NLP in Healthcare and Life Sciences Market by Component (Solutions and Services), NLP Type (Rule-based, Statistical, and Hybrid), Application (IVR, Predictive Risk Analytics), Organization Size, End User, and Region - Global Forecast to 2026
[317 Pages Report] The global NLP in healthcare and life sciences market size to grow from USD 1.8 billion in 2021 to USD 4.3 billion by 2026, at a Compound Annual Growth Rate (CAGR) of 19.0% during the forecast period. Factors such as growing need to analyze and extract insights from narrative text and huge amount of clinical data, increasing demand for improving EHR data usability to improve healthcare delivery and outcomes and the rising urge of predictive analytics technology to reduce risks and improve significant health concerns are driving the adoption of the NLP in healthcare and life sciences market across the globe.
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COVID-19 Impact
COVID-19 is disrupting the world, businesses, and economies, thus impacting on the livelihood of people live, their interaction, and the way they manage their businesses. The ability to sustain has become the new normal for enterprises as they shift their focus from growth opportunities and concentrate on implementing drastic measures to mitigate the impact of the COVID-19 pandemic. In the progressing fight against COVID-19, pharmaceutical and healthcare organizations, governments, and the broader scientific communities around the world are working to assess the impact of the virus, and quickly develop fast, accurate solutions. Few of the vendors in the market witness that NLP technology would enable fast, systematic, comprehensive insight generation from unstructured text. Sources can include scientific literature, clinical trial records, preprints, internal sources, medical records, social media, and news reports. Capturing the key information from these many sources, and synthesizing it into one Evidence Hub, deepens understanding for the users, which will accelerate outcomes. NLP has been extensively used in different organizations to categorize sentiments, perform recommendations, summarizing information, and topic modeling.
As the novel coronavirus has spread around the globe, it has created major disruption across communities, patients, and clinicians, the way they work, and how they engage in supporting stakeholders across the ecosystem. Pharmaceuticals and life sciences companies have found themselves front and center, providing extremely essential medical products to support patients in their time of need while also attracting widespread attention as the industry sprints to develop new therapeutics and vaccines for COVID-19.
Market Dynamics
Driver: Growing need to analyze and extract insights from narrative text and huge amount of clinical data
The shift in business models and outcome expectations is driving the need for better use of unstructured data. Traditional health information systems have focused on deriving value from 20% of the healthcare data that comes in the structured format through clinical channels. Hence, NLP can automatically derive patient information from free-form, unstructured text and produce actionable data that can be used to improve patient care and streamline workflow. Well-designed NLP systems can analyze text-free dictation, understand contexts, and tag the most critical clinical data elements such as problems, social history, medications, allergies, and procedures. Once tagged, these elements can be used to populate EHRs and other clinical IT systems, enabling applications that range from retrospective analysis across many medical records to support medical decisions for providing quality patient care.
NLP can be integrated as a part of physicians’ preferred work environment, supporting both real-time and background dictation workflows. For the real-time workflow, NLP can work with speech recognition technologies to capture narrative dictation and enable physicians to interactively self-edit texts and clinical facts as they appear on the EHR screen before committing information to EHRs. In the case of traditional background dictation/transcription workflow, NLP can be integrated with the workflow to process narrative and create rich clinical documents that include corrected texts and extracted clinical facts for physicians’ final review and approval. These finalized documents are processed in EHRs.
Restraint: Inadequacy in the advancements of NLP technology using neural networks restricting its usage for cloud-based services
NLP is a technology that uses neural networks and deep learning techniques for sequential data such as text, time series, financial data, speech, audio, and video. Neural networks and deep learning are the most advanced technologies that are paving the way for NLP to gain traction in the market. However, the development of these technologies is highly expensive and requires a huge investment in terms of R&D capital as well as time, which is not easy for small or startups companies that need to position themselves in the NLP in healthcare and life sciences market.
A neural network facilitates the accurate speech and voice recognition capabilities in NLP for higher capacity. It also computes the huge voice data generated by users to understand the context. However, neural network algorithms are expensive and complex and can only be managed by key players such as Apple (US), Microsoft (US), and Google (US). These major companies are using NLP technology to market their products and access cloud services provided by speech and voice recognition networks based on neural networks. Small players in the NLP in healthcare and life sciences market may not be able to heavily invest in the development of neural networks due to the high infrastructure cost involved. Hence, it restricts the market growth as small players are unable to contribute sufficiently.
Opportunity: The emergence of cognitive computing to boost the demand for NLP solutions for precision medicine applications
Semantic big data analytics and cognitive computing technologies have witnessed significant investments in the healthcare and life sciences industry from some recognizable players in the market. NLP has found applications in healthcare, ranging from the most cutting-edge solutions in precision medicine applications to the simple job of coding a claim for reimbursement or billing process. However, the key to the success of introducing this technology will be to develop algorithms that are intelligent, precise, and specific to ground-level issues in the healthcare and life sciences industry. NLP will have to meet the dual goals of data abstraction and data presentation so that patients can have an accurate record of their health in terms they can understand. This enriched solution would enhance physical efficiency and reduce operational costs within the healthcare space. The cognitive computing system processes enormous amounts of data instantly to answer specific queries and makes customized intelligent recommendations related to patient’s queries. It can also be used to compare patient having characteristics with cohorts of similar patients to find out which therapies work best. Another advantage of cognitive computing is its ability to link together several different kinds of data and analyze it in a context. This feature can help solve various IT challenges in healthcare and other industries.
Challenge: Growing regulatory compliance and privacy concerns over data security during COVID-19 slow down the progress of researchers
Clinical NLP has an immense potential to contribute to how clinical practices would be revolutionized by the advent of large-scale processing of clinical records. However, this potential has remained largely untapped due to the slow progress primarily caused due to strict data access policies for researchers. Data privacy has remained a major challenge in the adoption of AI among businesses. AI technologies process data and generate outputs. ML, deep learning, NLP, and emotion detection technologies feed on the stored data and provide actionable results. Users need to provide various data to carry out tasks with the help of smart devices or virtual personal assistants, such as Apple Siri and Amazon Alexa. Because of legal and institutional concerns arising from the sensitivity of clinical data, it is difficult for the NLP community to gain access to the relevant data. This, in turn, is especially true for researchers not connected with healthcare organizations. Clinical notes contain detailed information related to patient-clinician encounters in which patients confide not only their health complaints but also their lifestyle choices and stigmatized conditions. This confidential relationship is legally protected in the US by the Health Insurance Portability and Accountability Act (HIPAA) Privacy Rule in the case of individuals’ medical data. In the European Union (EU), the conditions for scientific usage of health data are set out in General Data Protection Regulation (GDPR). The sanitization of sensitive data categories and individuals’ informed consents are at the forefront of these legislative acts and bear immediate consequences for NLP research. Hence, the difficult access to data due to privacy concerns has been an obstacle to progress in the research field.
The solution segment is expected to account for a larger market size during the forecast period
The component segment has been further divided into solutions and services. Solution segments again bifurcated into clinical variation management, population health management, counter fraud management, and other solutions (claim management and risk adjustment); the services segment includes professional services and managed services. The solutions segment is expected to account for a larger market size during the forecast period. These solutions can be applied to the data collected from various sources to derive meaningful insights and make health decisions based on data. NLP in the healthcare industry can help to enhance the accuracy of EHRs and ensure completeness by transforming the free text into standardized data. This could also make documentation easier by allowing care providers to dictate notes, as NLP turns free text into documented data another favorable factor for the market.
North America to account for largest market size during the forecast period
North America is expected to have the largest market share in the NLP in healthcare and life sciences market. The early implementation of NLP solutions and rapid developments in IT infrastructure across healthcare sectors are the two major reasons behind the success of key vendors in the market in North America. The region has witnessed favorable conditions for the growth of the NLP in healthcare and life sciences market due to the positive approach of government regulations, startup funding, established player presence, and interest from enterprises to apply ML and NLP-based solutions.
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Key Market Players
The NLP in healthcare and life sciences vendors have implemented various types of organic and inorganic growth strategies, such as new product launches, product upgradations, partnerships and agreements, business expansions, and mergers and acquisitions to strengthen their offerings in the market. The major vendors in the global NLP in healthcare and life sciences market include Microsoft (US), Google (US), IBM (US), Cerner (US), 3M (US), AWS (US), Inovalon (US), Dolbey (US), Averbis (Germany), Linguamatics (an IQVIA Company) (UK), Apixio (US), Clinithink (US), Lexalytics (US), Apixio (US), Clinithink (US), Lexalytics (US), Health Fidelity (US), Wave Health Technologies (US), Corti (US), CloudMedx (US), Oncora Medical (US), Caption Health (US), ForeSee Medical (US), Press Ganey (US), Gnani.ai (India), Notable (US), Biofourmis (US), Babylon (UK), Flatiron (US), and Suki (US). The study includes an in-depth competitive analysis of these key players in the NLP in healthcare and life sciences market with their company profiles, recent developments, and key market strategies.
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Report Metrics |
Details |
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Market size available for years |
2017–2026 |
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Base year considered |
2021 |
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Forecast period |
2022–2026 |
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Forecast units |
USD Million |
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Segments covered |
Component, Deployment Mode, Organization Size, NLP Type, Application, End User, And Region |
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Geographies covered |
North America, Europe, APAC, Latin America and MEA |
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Companies covered |
Microsoft (US), Google (US), IBM (US), Cerner (US), 3M (US), AWS (US), Inovalon (US), Dolbey (US), Averbis (Germany), Linguamatics (an IQVIA Company) (UK), Apixio (US), Clinithink (US), Lexalytics (US), Apixio (US), Clinithink (US), Lexalytics (US), Health Fidelty (US), Wave Health Technologies (US), Corti (US), CloudMedx (US), Oncora Medical (US), Caption Health (US), ForeSee Medical (US), Press Ganey (US), Gnani.ai (India), Notable (US), Biofourmis (US), Babylon (UK), Flatiron (US), and Suki (US) |
This research report categorizes the NLP in healthcare and life sciences market based on components, deployment mode, organization size, NLP type, application, end user, and regions.
By Component:
- Solution
- Clinical Variation Management
- Population Health Management
- Counter Fraud Management
- Other Solutions (risk adjustment and claim management)
- Services
- Professional Services
- Managed Services
By Deployment Mode:
- Cloud
- On-premises
By Organization Size:
- Large enterprises
- Small and medium-sized enterprises (SMEs)
By NLP Type
- Rule-based
- Statistical
- Hybrid
By Application
- IVR
- Pattern and Image Recognition
- Summarization and Categorization
- Text and Speech Analytics
- Predictive Risk Analytics
- Reporting and Visualization
- Other Applications (question answering, sentiment analysis, spelling correction, and email filtration)
By End User
- NLP for Physician
- NLP for Patients
- NLP for Researchers
- NLP for Clinical Operators
By Region:
- North America
- US
- Canada
- Europe
- UK
- Germany
- France
- Rest of Europe
- APAC
- China
- Singapore
- India
- Rest of APAC
- MEA
- KSA
- UAE
- South Africa
- Rest of MEA
- Latin America
- Brazil
- Mexico
- Rest of Latin America
Recent Developments:
- In May 2021, IBM partnered with Gratitude to combine IBM Watson Health and Graticule. This integration will offer real-world evidence solutions that will help life science organizations to solve challenges in rare disease research, such as clinical trial recruitment, creating external control arms, and treatment reimbursement.
- In May 2021, Google partnered with HCA Healthcare to create a new data analytics platform that will leverage information from the health system’s 32 million annual patient encounters.
- In April 2021, Microsoft announced the intent to acquire Nuance for USD 19.7 billion. This acquisition will provide more depth and breadth in healthcare provider space, enterprise customer care, and enterprise cloud services for companies using Microsoft and Nuance.
- In June 2020, 3M partnered with MIT for developing new low-cost, rapid diagnostic tests for COVID-19. The project is part of the RADx Tech program created by the National Institute of Health (NIH) specifically to fund the development of tests that can expand US testing deployment.
- In May 2020, Microsoft collaborated with UnitedHealth Group to launch the ProtectWell protocol and app to support return-to-workplace planning and COVID-19 symptom screening. ProtectWell combines UnitedHealth Group’s clinical and data analytics capabilities with Microsoft’s technology leadership to help in the next phases of COVID-19 recovery efforts.
- In April 2020, Google and Apple collaborated to enable Bluetooth technology to help government and healthcare agencies reduce the spread of COVID-19. This enabled a broader Bluetooth-based contact tracing platform.
Frequently Asked Questions (FAQ):
What is NLP in healthcare and life sciences?
According to ForeSee Medical, NLP is the ability of computers to understand the latest human speech terms and text. It is used in current technology to support spam email privacy, personal voice assistants, and language translation applications. The adoption of NLP in healthcare and life sciences is rising because of its recognized potential to search, analyze, and interpret a mammoth amount of patient datasets. Using advanced NLP-based algorithms, healthcare and life sciences firms harness the relevant insights and concepts from the clinical data that was previously considered buried in the text form.
Which countries are considered in the European region?
The report includes an analysis of the UK, Germany, France and other European countries in the European region.
Which are key applications leveraging NLP in healthcare and life sciences and services?
Key application leveraging NLP in healthcare and life sciences and services include IVR, pattern and image recognition, summarization and categorization, text and speech analytics, predictive risk analytics, reporting and visualization, and other applications (question answering, sentiment analysis, spelling correction, and email filtration).
Which are the key drivers supporting the growth of the NLP in healthcare and life sciences market?
The key drivers supporting the growth of the NLP in healthcare and life sciences market include the rising urge of predictive analytics technology to reduce risks and improve significant health concerns, growing demand for improving EHR data usability to improve healthcare delivery and outcomes, and increasing need to analyze and extract insights from narrative text and huge amount of clinical data.
Who are the key vendors in the NLP in healthcare and life sciences market?
The key vendors operating in the NLP in healthcare and life sciences market are Microsoft (US), Google (US), IBM (US), Cerner (US), 3M (US), AWS (US), Inovalon (US), Dolbey (US), Averbis (Germany), Linguamatics (an IQVIA Company) (UK), Apixio (US), Clinithink (US), Lexalytics (US), Apixio (US), Clinithink (US), Lexalytics (US), Health Fidelty (US), Wave Health Technologies (US), Corti (US), CloudMedx (US), Oncora Medical (US), Caption Health (US), ForeSee Medical (US), Press Ganey (US), Gnani.ai (India), Notable (US), Biofourmis (US), Babylon (UK), Flatiron (US), and Suki (US). These vendors have adopted different types of organic and inorganic growth strategies such as new product launches, product enhancements, partnerships, and mergers and acquisitions. .
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TABLE OF CONTENTS
1 INTRODUCTION (Page No. - 50)
1.1 INTRODUCTION TO COVID-19
1.2 COVID-19 HEALTH ASSESSMENT
FIGURE 1 COVID-19: GLOBAL PROPAGATION
FIGURE 2 COVID-19 PROPAGATION: SELECT COUNTRIES
1.3 COVID-19 ECONOMIC ASSESSMENT
FIGURE 3 REVISED GROSS DOMESTIC PRODUCT FORECASTS FOR SELECT G20 COUNTRIES IN 2020
1.3.1 COVID-19 ECONOMIC IMPACT—SCENARIO ASSESSMENT
FIGURE 4 CRITERIA IMPACTING GLOBAL ECONOMY
FIGURE 5 SCENARIOS IN TERMS OF RECOVERY OF GLOBAL ECONOMY
1.4 OBJECTIVES OF THE STUDY
1.5 MARKET DEFINITION
1.5.1 INCLUSIONS AND EXCLUSIONS
1.6 MARKET SCOPE
1.6.1 MARKET SEGMENTATION
1.6.2 YEARS CONSIDERED FOR THE STUDY
1.7 CURRENCY CONSIDERED
TABLE 1 UNITED STATES DOLLAR EXCHANGE RATE, 2018–2020
1.8 STAKEHOLDERS
2 RESEARCH METHODOLOGY (Page No. - 59)
2.1 RESEARCH DATA
FIGURE 6 NLP IN HEALTHCARE AND LIFE SCIENCES MARKET: RESEARCH DESIGN
2.1.1 SECONDARY DATA
2.1.2 PRIMARY DATA
TABLE 2 PRIMARY INTERVIEWS
2.1.2.1 Breakup of primary profiles
2.1.2.2 Key industry insights
2.2 MARKET BREAKUP AND DATA TRIANGULATION
FIGURE 7 DATA TRIANGULATION
2.3 MARKET SIZE ESTIMATION
FIGURE 8 NLP IN HEALTHCARE AND LIFE SCIENCES MARKET: TOP-DOWN AND BOTTOM-UP APPROACHES
2.3.1 TOP-DOWN APPROACH
2.3.2 BOTTOM-UP APPROACH
FIGURE 9 MARKET SIZE ESTIMATION METHODOLOGY - APPROACH 1 (SUPPLY-SIDE): REVENUE FROM SOLUTIONS/SERVICES OF THE NLP IN THE HEALTHCARE AND LIFE SCIENCES MARKET
FIGURE 10 MARKET SIZE ESTIMATION METHODOLOGY - APPROACH 2, BOTTOM-UP (SUPPLY-SIDE): COLLECTIVE REVENUE FROM ALL SOLUTIONS/SERVICES OF THE NLP IN THE HEALTHCARE AND LIFE SCIENCES MARKET
FIGURE 11 MARKET SIZE ESTIMATION METHODOLOGY - APPROACH 3, BOTTOM-UP (SUPPLY-SIDE): COLLECTIVE REVENUE FROM ALL SOLUTIONS/SERVICES OF THE NLP IN THE HEALTHCARE AND LIFE SCIENCES MARKET
FIGURE 12 MARKET SIZE ESTIMATION METHODOLOGY - APPROACH 4, BOTTOM-UP (DEMAND-SIDE): COMPONENT LEVEL SHARE THROUGH OVERALL NLP IN HEALTHCARE AND LIFE SCIENCES SPENDING
2.4 MARKET FORECAST
TABLE 3 FACTOR ANALYSIS
2.5 COMPANY EVALUATION MATRIX METHODOLOGY
FIGURE 13 COMPANY EVALUATION MATRIX: CRITERIA WEIGHTAGE
2.6 STARTUP/SME EVALUATION MATRIX METHODOLOGY
FIGURE 14 STARTUP/SME EVALUATION MATRIX: CRITERIA WEIGHTAGE
2.7 ASSUMPTIONS FOR THE STUDY
2.8 LIMITATIONS OF THE STUDY
2.9 IMPLICATIONS OF COVID-19 ON THE NLP IN HEALTHCARE AND LIFE SCIENCES MARKET
FIGURE 15 QUARTERLY IMPACT OF COVID-19 DURING 2020–2021
3 EXECUTIVE SUMMARY (Page No. - 76)
TABLE 4 GLOBAL NLP IN HEALTHCARE AND LIFE SCIENCES MARKET SIZE AND GROWTH RATE, 2017–2020 (USD MILLION, Y-O-Y %)
TABLE 5 GLOBAL MARKET SIZE AND GROWTH RATE, 2021–2026 (USD MILLION, Y-O-Y %)
FIGURE 16 SOLUTIONS SEGMENT TO DOMINATE THE MARKET IN 2021
FIGURE 17 PROFESSIONAL SERVICES TO HOLD A LARGER MARKET SHARE OF THE MARKET IN 2021
FIGURE 18 SYSTEM INTEGRATION AND IMPLEMENTATION SEGMENT TO DOMINATE THE MARKET IN 2021
FIGURE 19 STATISTICAL SEGMENT TO HOLD THE LARGEST MARKET SHARE IN THE MARKET IN 2021
FIGURE 20 INTERACTIVE VOICE RESPONSE SEGMENT TO BE THE LARGEST APPLICATION SEGMENT IN THE MARKET IN 2021
FIGURE 21 CLINICAL VARIATION MANAGEMENT SEGMENT TO ACCOUNT FOR THE LARGEST MARKET SHARE IN 2021
FIGURE 22 CLOUD SEGMENT TO HOLD A LARGER MARKET SHARE IN 2021
FIGURE 23 LARGE ENTERPRISES TO DOMINATE THE NLP IN HEALTHCARE AND LIFE SCIENCES MARKET IN 2021
FIGURE 24 NLP FOR RESEARCHERS SEGMENT TO GROW AT THE HIGHEST CAGR IN 2021
FIGURE 25 NORTH AMERICA TO HOLD THE LARGEST MARKET SHARE AND ASIA PACIFIC TO GROW AT THE HIGHEST CAGR IN THE MARKET IN 2021
4 PREMIUM INSIGHTS (Page No. - 82)
4.1 ATTRACTIVE OPPORTUNITIES IN THE NLP IN HEALTHCARE AND LIFE SCIENCES MARKET
FIGURE 26 GROWING DEMAND TO IMPROVE ELECTRONIC HEALTHCARE DATA USABILITY FOR BETTER HEALTHCARE DELIVERY AND BUSINESS OUTCOMES TO DRIVE MARKET GROWTH
4.2 MARKET: TOP THREE APPLICATIONS
FIGURE 27 PATTERN AND IMAGE RECOGNITION SEGMENT TO GROW AT THE HIGHEST CAGR DURING THE FORECAST PERIOD
4.3 NORTH AMERICA: MARKET, BY COMPONENT AND TOP THREE APPLICATIONS
FIGURE 28 SOLUTIONS SEGMENT AND INTERACTIVE VOICE RESPONSE SEGMENT TO HOLD THE LARGEST MARKET SHARES IN NORTH AMERICA 2021
4.4 MARKET: BY REGION
FIGURE 29 NORTH AMERICA TO HOLD THE LARGEST MARKET SHARE IN 2021
5 MARKET OVERVIEW AND INDUSTRY TRENDS (Page No. - 84)
5.1 INTRODUCTION
5.2 MARKET DYNAMICS
FIGURE 30 DRIVERS, RESTRAINTS, OPPORTUNITIES, AND CHALLENGES: NLP IN HEALTHCARE AND LIFE SCIENCES MARKET
5.2.1 DRIVERS
5.2.1.1 The rising urge of predictive analytics technology to reduce risks and improve significant health concerns
5.2.1.2 Growing demand for improving EHR data usability to improve healthcare delivery and outcomes
5.2.1.3 Growing need to analyze and extract insights from narrative text and huge amount of clinical data
5.2.2 RESTRAINTS
5.2.2.1 Specific medical sub-languages and poor input data quality
5.2.2.2 Inadequacy in the advancements of NLP technology using neural networks restricting its usage for cloud-based services
5.2.3 OPPORTUNITIES
5.2.3.1 Ensemble NLP systems to boost phenotyping capabilities
5.2.3.2 Rising demand for NLP systems programmed to understand the context of medical records
5.2.3.3 The emergence of cognitive computing to boost the demand for NLP solutions for precision medicine applications
5.2.4 CHALLENGES
5.2.4.1 Growing regulatory compliance and privacy concerns over data security during COVID-19 slow down the progress of researchers
5.2.4.2 Interoperability and reliability issues while deploying NLP algorithms
5.2.5 CUMULATIVE GROWTH ANALYSIS
5.3 NLP IN HEALTHCARE AND LIFE SCIENCES: ECOSYSTEM
FIGURE 31 ECOSYSTEM OF THE NLP IN HEALTHCARE AND LIFE SCIENCES MARKET
5.4 CASE STUDY ANALYSIS
5.4.1 DREXEL UNIVERSITY USED LINGUAMATICS I2E TO IMPROVE COHORT SELECTION FOR HIV AND HEPATITIS C
5.4.2 A HEALTHCARE COMPANY USED AXTRIA TO PROVIDE A COMPREHENSIVE VIEW OF PATIENT REPORTS AND DELIVER CRITICAL INSIGHTS TO BOTH HEALTHCARE PROVIDERS AND THE COMPANY
5.4.3 TO CREATE A DATABASE AND MEDICAL KNOWLEDGE BASE FOR AN ONLINE CLINIC CHATBOT TO BUILD UP ANAMNESIS
5.4.4 LEADING RENAL CARE PROVIDERS IMPLEMENT CITIUSTECH SOLUTION TO PREDICT HIGH-RISK CHRONIC KIDNEY DISEASE
5.4.5 HEALTH SYSTEM APPLIES LINGUAMATICS NLP PLATFORM TO IMPROVE PATIENT CARE AND GAIN INSIGHTS FROM POPULATION HEALTH DATA
5.4.6 LEADING HEALTHCARE PAYERS IMPLEMENTED LINGUAMATICS NLP SOLUTIONS TO GAIN INSIGHTS FROM THE UNSTRUCTURED DATA
5.4.7 MEDTRONIC BUILDS A MOBILE PERSONAL ASSISTANT APP FOR DIABETES MANAGEMENT
5.4.8 PRIMARY MEDICAL CARE GROUP ENGAGED FORESEE MEDICAL TO THE ESP RISK ADJUSTMENT SOFTWARE FOR IMPROVING PROFITABILITY
5.4.9 FLAGLER HEALTH IMPROVES THE EXPERIENCE OF CLINICAL DOCUMENTATION FOR RADIOLOGISTS
5.5 NLP IN HEALTHCARE AND LIFE SCIENCES MARKET: COVID-19 IMPACT
FIGURE 32 MARKET TO WITNESS MINIMAL SLOWDOWN IN GROWTH IN 2020
5.6 NLP IN HEALTHCARE AND LIFE SCIENCES: ARCHITECTURE
FIGURE 33 FUNCTIONAL ELEMENTS OF NLP IN HEALTHCARE AND LIFE SCIENCES SOLUTIONS
5.7 TECHNOLOGY ANALYSIS: NLP IN HEALTHCARE AND LIFE SCIENCES MARKET
5.7.1 HEALTHCARE TRACKERS, WEARABLES, AND SENSORS
5.7.2 VIRTUAL REALITY
5.7.3 AUGMENTED REALITY
5.7.4 3D PRINTING
5.7.5 ROBOTICS
5.7.6 NANOTECHNOLOGY
5.8 REGULATORY IMPLICATIONS
5.8.1 GENERAL DATA PROTECTION REGULATION
5.8.2 HEALTH LEVEL SEVEN
5.8.3 HEALTH INSURANCE PORTABILITY AND ACCOUNTABILITY ACT OF 1996
5.8.4 CEN ISO/IEEE 11073
5.8.5 HIPAA SECURITY RULE
5.8.6 HIPAA PRIVACY RULE
5.9 PATENT ANALYSIS
5.9.1 METHODOLOGY
5.9.2 DOCUMENT TYPE
TABLE 6 PATENTS FILED, 2018–2021
5.9.3 INNOVATION AND PATENT APPLICATIONS
FIGURE 34 TOTAL NUMBER OF PATENTS GRANTED OVER THE LAST THREE YEARS (2018–2021)
5.9.3.1 Top applicants
FIGURE 35 TOP 10 COMPANIES WITH THE HIGHEST NUMBER OF PATENT APPLICATIONS, 2018–2021
5.10 SUPPLY CHAIN ANALYSIS
FIGURE 36 SUPPLY CHAIN ANALYSIS
TABLE 7 NLP IN HEALTHCARE AND LIFE SCIENCES MARKET: SUPPLY CHAIN
5.11 PRICING MODEL ANALYSIS
TABLE 8 PRICING MODEL OF NLP IN HEALTHCARE AND LIFE SCIENCES PLAYERS: 2019–2020
5.12 PORTER’S FIVE FORCES ANALYSIS
TABLE 9 IMPACT OF EACH FORCE ON NLP IN HEALTHCARE AND LIFE SCIENCES
FIGURE 37 PORTER’S FIVE FORCES ANALYSIS
5.12.1 THREAT OF NEW ENTRANTS
5.12.2 THREAT OF SUBSTITUTES
5.12.3 BARGAINING POWER OF SUPPLIERS
5.12.4 BARGAINING POWER OF BUYERS
5.12.5 INTENSITY OF COMPETITIVE RIVALRY
5.13 SCENARIO
TABLE 10 CRITICAL FACTORS TO IMPACT THE GROWTH OF THE NLP IN THE HEALTHCARE AND LIFE SCIENCES MARKET
6 NLP IN HEALTHCARE AND LIFE SCIENCES MARKET, BY COMPONENT (Page No. - 110)
6.1 INTRODUCTION
6.1.1 COMPONENTS: COVID-19 IMPACT
FIGURE 38 SERVICES TO REGISTER A HIGHER CAGR DURING THE FORECAST PERIOD
TABLE 11 MARKET, BY COMPONENT, 2017–2020 (USD MILLION)
TABLE 12 MARKET, BY COMPONENT, 2021–2026 (USD MILLION)
6.2 SOLUTIONS
TABLE 13 SOLUTIONS: MARKET, BY REGION, 2017–2020 (USD MILLION)
TABLE 14 SOLUTIONS: NLP IN HEALTHCARE AND LIFE SCIENCES MARKET, BY REGION, 2021–2026 (USD MILLION)
FIGURE 39 COUNTER FRAUD MANAGEMENT SOLUTIONS TO REGISTER THE HIGHEST CAGR DURING THE FORECAST PERIOD
TABLE 15 NLP IN HEALTHCARE AND LIFE SCIENCES SOLUTIONS MARKET, BY TYPE, 2017–2020 (USD MILLION)
TABLE 16 NLP IN HEALTHCARE AND LIFE SCIENCES SOLUTIONS MARKET, BY TYPE, 2021–2026 (USD MILLION)
6.2.1 CLINICAL VARIATION MANAGEMENT
6.2.1.1 The need to analyze and process heterogeneous variations in clinical notes to drive NLP adoption for clinical variation management
TABLE 17 CLINICAL VARIATION MANAGEMENT: NLP IN HEALTHCARE AND LIFE SCIENCES MARKET, BY REGION, 2017–2020 (USD MILLION)
TABLE 18 CLINICAL VARIATION MANAGEMENT: MARKET, BY REGION, 2021–2026 (USD MILLION)
6.2.2 POPULATION HEALTH MANAGEMENT
6.2.2.1 The need to analyze unstructured data for deriving insights about non-healthcare factors affecting population health to drive the adoption of NLP for population health management
TABLE 19 POPULATION HEALTH MANAGEMENT: MARKET, BY REGION, 2017–2020 (USD MILLION)
TABLE 20 POPULATION HEALTH MANAGEMENT: MARKET, BY REGION, 2021–2026 (USD MILLION)
6.2.3 COUNTER FRAUD MANAGEMENT
6.2.3.1 Increasing frauds in the healthcare sector due to complex and bureaucratic processes to drive the adoption of NLP solutions for counter fraud management
TABLE 21 COUNTER FRAUD MANAGEMENT: NLP IN HEALTHCARE AND LIFE SCIENCES MARKET, BY REGION, 2017–2020 (USD MILLION)
TABLE 22 COUNTER FRAUD MANAGEMENT: MARKET, BY REGION, 2021–2026 (USD MILLION)
6.2.4 OTHER SOLUTIONS
TABLE 23 OTHER SOLUTIONS: MARKET, BY REGION, 2017–2020 (USD MILLION)
TABLE 24 OTHER SOLUTIONS: MARKET, BY REGION, 2021–2026 (USD MILLION)
6.3 SERVICES
FIGURE 40 MANAGED SERVICES TO GROW AT A HIGHER CAGR DURING THE FORECAST PERIOD
TABLE 25 SERVICES: MARKET, BY REGION, 2017–2020 (USD MILLION)
TABLE 26 SERVICES: MARKET, BY REGION, 2021–2026 (USD MILLION)
TABLE 27 SERVICES: MARKET, BY TYPE, 2017–2020 (USD MILLION)
TABLE 28 SERVICES: NLP IN HEALTHCARE AND LIFE SCIENCES MARKET, BY TYPE, 2021–2026 (USD MILLION)
6.3.1 PROFESSIONAL SERVICES
6.3.1.1 The need to understand unstructured data for enhancing enterprise insight discovery, analytics, and decision-making to drive the reliance on professional services
FIGURE 41 TRAINING AND CONSULTING SEGMENT TO GROW AT THE HIGHEST CAGR DURING THE FORECAST PERIOD
TABLE 29 PROFESSIONAL SERVICES: MARKET, BY TYPE, 2017–2020 (USD MILLION)
TABLE 30 PROFESSIONAL SERVICES: MARKET, BY TYPE, 2021–2026 (USD MILLION)
TABLE 31 PROFESSIONAL SERVICES: MARKET, BY REGION, 2017–2020 (USD MILLION)
TABLE 32 PROFESSIONAL SERVICES: NLP IN HEALTHCARE AND LIFE SCIENCES MARKET, BY REGION, 2021–2026 (USD MILLION)
6.3.1.2 Training and consulting
TABLE 33 TRAINING AND CONSULTING: MARKET, BY REGION, 2017–2020 (USD MILLION)
TABLE 34 TRAINING AND CONSULTING: MARKET, BY REGION, 2021–2026 (USD MILLION)
6.3.1.3 Support and maintenance
TABLE 35 SUPPORT AND MAINTENANCE: MARKET, BY REGION, 2017–2020 (USD MILLION)
TABLE 36 SUPPORT AND MAINTENANCE: MARKET, BY REGION, 2021–2026 (USD MILLION)
6.3.1.4 System integration and implementation
TABLE 37 SYSTEM INTEGRATION AND IMPLEMENTATION: MARKET, BY REGION, 2017–2020 (USD MILLION)
TABLE 38 SYSTEM INTEGRATION AND IMPLEMENTATION: MARKET, BY REGION, 2021–2026 (USD MILLION)
6.3.2 MANAGED SERVICES
6.3.2.1 Customization needs due to ongoing demands and alterations in solutions support managed services
TABLE 39 MANAGED SERVICES: MARKET, BY REGION, 2017–2020 (USD MILLION)
TABLE 40 MANAGED SERVICES: MARKET, BY REGION, 2021–2026 (USD MILLION)
7 NLP IN HEALTHCARE AND LIFE SCIENCES MARKET, BY DEPLOYMENT MODE (Page No. - 126)
7.1 INTRODUCTION
7.1.1 DEPLOYMENT MODES: COVID-19 IMPACT
FIGURE 42 CLOUD SEGMENT TO REGISTER A HIGHER CAGR DURING THE FORECAST PERIOD
TABLE 41 MARKET, BY DEPLOYMENT MODE, 2017–2020 (USD MILLION)
TABLE 42 MARKET, BY DEPLOYMENT MODE, 2021–2026 (USD MILLION)
7.2 CLOUD
7.2.1 REDUCED OPERATIONAL COSTS AND HIGHER SCALABILITY TO SUPPORT THE GROWTH OF THIS SEGMENT
TABLE 43 CLOUD: MARKET, BY REGION, 2017–2020 (USD MILLION)
TABLE 44 CLOUD: MARKET, BY REGION, 2021–2026 (USD MILLION)
7.3 ON-PREMISES
7.3.1 EASE OF INTEGRATION OF DATA WITH THE EXISTING APPLICATIONS AND DATABASES RESULTED IN THE INCREASED ADOPTION OF ON-PREMISES NLP SOLUTIONS
TABLE 45 ON-PREMISES: MARKET, BY REGION, 2017–2020 (USD MILLION)
TABLE 46 ON-PREMISES: MARKET, BY REGION, 2021–2026 (USD MILLION)
8 NLP IN HEALTHCARE AND LIFE SCIENCES MARKET, BY ORGANIZATION SIZE (Page No. - 131)
8.1 INTRODUCTION
8.1.1 ORGANIZATION SIZE: COVID-19 IMPACT
FIGURE 43 SMALL AND MEDIUM-SIZED ENTERPRISES SEGMENT TO REGISTER A HIGHER CAGR DURING THE FORECAST PERIOD
TABLE 47 MARKET, BY ORGANIZATION SIZE, 2017–2020 (USD MILLION)
TABLE 48 MARKET, BY ORGANIZATION SIZE, 2021–2026 (USD MILLION)
8.2 LARGE ENTERPRISES
8.2.1 LARGE ENTERPRISES ARE INCREASINGLY INTEGRATING DISPARATE DATA INTO MEANINGFUL SOURCES FOR AI ALGORITHMS
TABLE 49 LARGE ENTERPRISES: MARKET, BY REGION, 2017–2020 (USD MILLION)
TABLE 50 LARGE ENTERPRISES: MARKET, BY REGION, 2021–2026 (USD MILLION)
8.3 SMALL AND MEDIUM-SIZED ENTERPRISES
8.3.1 SMALL AND MEDIUM-SIZED ENTERPRISES ARE AT AN EARLY STAGE OF NLP ADOPTION
TABLE 51 SMALL AND MEDIUM-SIZED ENTERPRISES: MARKET, BY REGION, 2017–2020 (USD MILLION)
TABLE 52 SMALL AND MEDIUM-SIZED ENTERPRISES: MARKET, BY REGION, 2021–2026 (USD MILLION)
9 NLP IN HEALTHCARE AND LIFE SCIENCES MARKET, BY NLP TYPE (Page No. - 136)
9.1 INTRODUCTION
9.1.1 NLP TYPES: COVID-19 IMPACT
FIGURE 44 STATISTICAL SEGMENT TO WITNESS THE HIGHEST GROWTH RATE DURING THE FORECAST PERIOD
TABLE 53 MARKET, BY NLP TYPE, 2017–2020 (USD MILLION)
TABLE 54 MARKET, BY NLP TYPE, 2021–2026 (USD MILLION)
9.2 RULE-BASED NATURAL LANGUAGE PROCESSING
9.2.1 HIGH ACCURACY PROVIDED BY RULE-BASED NLP MODELS TO DRIVE MARKET GROWTH
TABLE 55 RULE-BASED: MARKET, BY REGION, 2017–2020 (USD MILLION)
TABLE 56 RULE-BASED: MARKET, BY REGION, 2021–2026 (USD MILLION)
9.3 STATISTICAL NATURAL LANGUAGE PROCESSING
9.3.1 THIS APPROACH IS WIDELY IMPLEMENTED IN SENTIMENT ANALYSIS AND INFORMATION EXTRACTION
TABLE 57 STATISTICAL: NLP IN HEALTHCARE AND LIFE SCIENCES MARKET, BY REGION, 2017–2020 (USD MILLION)
TABLE 58 STATISTICAL: MARKET, BY REGION, 2021–2026 (USD MILLION)
9.4 HYBRID NATURAL LANGUAGE PROCESSING
9.4.1 HYBRID MODELS OFFER BENEFITS SUCH AS HIGH ACCURACY, BETTER SPEED, ROBUSTNESS, AND RELIABILITY
TABLE 59 HYBRID: MARKET, BY REGION, 2017–2020 (USD MILLION)
TABLE 60 HYBRID: MARKET, BY REGION, 2021–2026 (USD MILLION)
10 NLP IN HEALTHCARE AND LIFE SCIENCES MARKET, BY APPLICATION (Page No. - 142)
10.1 INTRODUCTION
10.1.1 APPLICATIONS: COVID-19 IMPACT
FIGURE 45 PATTERN AND IMAGE RECOGNITION SEGMENT TO REGISTER THE HIGHEST CAGR DURING THE FORECAST PERIOD
TABLE 61 MARKET, BY APPLICATION, 2017–2020 (USD MILLION)
TABLE 62 MARKET, BY APPLICATION, 2021–2026 (USD MILLION)
10.2 INTERACTIVE VOICE RESPONSE
10.2.1 ADOPTION OF VIRTUAL CARE DELIVERY AND PAYMENTS DIGITIZATION FOR COVID-19 HEALTHCARE SERVICES CONTRIBUTES TO THE GROWTH OF INTERACTIVE VOICE RESPONSE
TABLE 63 INTERACTIVE VOICE RESPONSE: MARKET, BY REGION, 2017–2020 (USD MILLION)
TABLE 64 INTERACTIVE VOICE RESPONSE: NLP IN HEALTHCARE AND LIFE SCIENCES MARKET, BY REGION, 2021–2026 (USD MILLION)
10.3 SUMMARIZATION AND CATEGORIZATION
10.3.1 THE NEED FOR INTELLIGENT PROCESSING OF UNSTRUCTURED HEALTH-RELATED DATA TO EXTRACT KNOWLEDGE TO DRIVE THE ADOPTION OF NLP FOR SUMMARIZATION AND CATEGORIZATION
TABLE 65 SUMMARIZATION AND CATEGORIZATION: MARKET, BY REGION, 2017–2020 (USD MILLION)
TABLE 66 SUMMARIZATION AND CATEGORIZATION: MARKET, BY REGION, 2021–2026 (USD MILLION)
10.4 REPORTING AND VISUALIZATION
10.4.1 FOCUS ON IDENTIFYING KEY INFORMATION AND AUTOMATICALLY ASSIGNING MEDICAL CODES FOR CONSISTENT REPORTING TO DRIVE THE ADOPTION OF NLP FOR REPORTING AND VISUALIZATION
TABLE 67 REPORTING AND VISUALIZATION: NLP IN HEALTHCARE AND LIFE SCIENCES MARKET, BY REGION, 2017–2020 (USD MILLION)
TABLE 68 REPORTING AND VISUALIZATION: MARKET, BY REGION, 2021–2026 (USD MILLION)
10.5 PREDICTIVE RISK ANALYTICS
10.5.1 THE NEED TO GENERATE PATIENT RISK SCORES TO DETECT EARLY SIGNS OF PATIENT DETERIORATION AND IDENTIFY AT-RISK PATIENTS TO DRIVE THE ADOPTION OF NLP FOR PREDICTIVE RISK ANALYTICS
TABLE 69 PREDICTIVE RISK ANALYTICS: MARKET, BY REGION, 2017–2020 (USD MILLION)
TABLE 70 PREDICTIVE RISK ANALYTICS: MARKET, BY REGION, 2021–2026 (USD MILLION)
10.6 PATTERN AND IMAGE RECOGNITION
10.6.1 THE DEVELOPMENT OF ADVANCED TOOLS, SUCH AS COMPUTER VISION MODELS, TO ANALYZE IMAGES AND SPECIMENS TO DRIVE THE ADOPTION
TABLE 71 PATTERN AND IMAGE RECOGNITION: MARKET, BY REGION, 2017–2020 (USD MILLION)
TABLE 72 PATTERN AND IMAGE RECOGNITION: NLP IN HEALTHCARE AND LIFE SCIENCES MARKET SIZE, BY REGION, 2021–2026 (USD MILLION)
10.7 TEXT AND SPEECH ANALYTICS
10.7.1 NLP TEXT ANALYTICS ENABLES USERS TO TRANSFORM THE UNSTRUCTURED DATA, SUCH AS FREE-TEXT CLINICAL NOTES, INTO THE STRUCTURED DATA TO PROVIDE INSIGHTS
TABLE 73 TEXT AND SPEECH ANALYTICS: MARKET, BY REGION, 2017–2020 (USD MILLION)
TABLE 74 TEXT AND SPEECH ANALYTICS: MARKET, BY REGION, 2021–2026 (USD MILLION)
10.8 OTHER APPLICATIONS
TABLE 75 OTHER APPLICATIONS: MARKET, BY REGION, 2017–2020 (USD MILLION)
TABLE 76 OTHER APPLICATIONS: MARKET, BY REGION, 2021–2026 (USD MILLION)
11 NLP IN HEALTHCARE AND LIFE SCIENCES MARKET, BY END USER (Page No. - 154)
11.1 INTRODUCTION
11.1.1 END USERS: COVID-19 IMPACT
FIGURE 46 NLP FOR RESEARCHERS SEGMENT TO GROW AT THE HIGHEST CAGR DURING THE FORECAST PERIOD
TABLE 77 MARKET, BY END USER, 2017–2020 (USD MILLION)
TABLE 78 MARKET, BY END USER, 2021–2026 (USD MILLION)
11.2 NLP FOR PATIENTS
11.2.1 THE NEED TO REDUCE HESITATION OF PATIENTS TO COMMUNICATE THEIR HEALTH CONCERNS TO LEAD THE ADOPTION OF NLP FOR PATIENTS, ESPECIALLY CHATBOTS
TABLE 79 NLP FOR PATIENTS: MARKET, BY REGION, 2017–2020 (USD MILLION)
TABLE 80 NLP FOR PATIENTS: MARKET, BY REGION, 2021–2026 (USD MILLION)
11.3 NLP FOR PHYSICIANS
11.3.1 NLP SEES GROWING ADOPTION TO AUTOMATE BACK-END TASKS FOR PHYSICIANS, GIVING THEM MORE TIME TO ATTEND TO PATIENTS’ CONCERNS
TABLE 81 NLP FOR PHYSICIANS: NLP IN HEALTHCARE AND LIFE SCIENCES MARKET, BY REGION, 2017–2020 (USD MILLION)
TABLE 82 NLP FOR PHYSICIANS: MARKET, BY REGION, 2021–2026 (USD MILLION)
11.4 NLP FOR RESEARCHERS
11.4.1 THE NEED TO OVERCOME THE BARRIER OF ANALYZING QUALITATIVE DATA AND REDUCE THE TIME REQUIRED FOR ANALYZING LARGE COLLECTIONS OF TEXT DATA TO DRIVE THE ADOPTION OF NLP FOR RESEARCHERS
TABLE 83 NLP FOR RESEARCHERS: MARKET, BY REGION, 2017–2020 (USD MILLION)
TABLE 84 NLP FOR RESEARCHERS: MARKET, BY REGION, 2021–2026 (USD MILLION)
11.5 NLP FOR CLINICAL OPERATORS
11.5.1 NLP ENABLES RENDERING OF UNSTRUCTURED RECORDS TO INCREASE AWARENESS RELATED TO EARLY SIGNS AND SYMPTOMS IN PATIENTS AND INTIMATE CLINICIANS LEADING TO THE ADOPTION OF NLP FOR CLINICAL OPERATIONS
TABLE 85 NLP FOR CLINICAL OPERATORS: NLP IN HEALTHCARE AND LIFE SCIENCES MARKET, BY REGION, 2017–2020 (USD MILLION)
TABLE 86 NLP FOR CLINICAL OPERATORS: MARKET, BY REGION, 2021–2026 (USD MILLION)
12 NATURAL LANGUAGE PROCESSING IN HEALTHCARE AND LIFE SCIENCES MARKET, BY REGION (Page No. - 161)
12.1 INTRODUCTION
12.2 NORTH AMERICA
12.2.1 NORTH AMERICA: COVID-19 IMPACT
12.2.2 NORTH AMERICA: REGULATIONS
12.2.2.1 Gramm–Leach–Bliley Act
12.2.2.2 Federal Information Security Management Act
12.2.2.3 Federal Information Processing Standards
12.2.2.4 California Consumer Privacy Act (CSPA)
FIGURE 47 NORTH AMERICA: MARKET SNAPSHOT
FIGURE 48 ASIA PACIFIC SEGMENT TO GROW AT THE HIGHEST CAGR DURING THE FORECAST PERIOD
FIGURE 49 INDIA TO GROW AT THE HIGHEST CAGR DURING THE FORECAST PERIOD
TABLE 87 NORTH AMERICA: NLP IN HEALTHCARE AND LIFE SCIENCES MARKET, BY COMPONENT, 2017–2020 (USD MILLION)
TABLE 88 NORTH AMERICA: MARKET, BY COMPONENT, 2021–2026 (USD MILLION)
TABLE 89 NORTH AMERICA: MARKET, BY SOLUTION, 2017–2020 (USD MILLION)
TABLE 90 NORTH AMERICA: MARKET, BY SOLUTION, 2021–2026 (USD MILLION)
TABLE 91 NORTH AMERICA: MARKET, BY SERVICE, 2017–2020 (USD MILLION)
TABLE 92 NORTH AMERICA: MARKET, BY SERVICE, 2021–2026 (USD MILLION)
TABLE 93 NORTH AMERICA: MARKET, BY PROFESSIONAL SERVICE, 2017–2020 (USD MILLION)
TABLE 94 NORTH AMERICA: MARKET, BY PROFESSIONAL SERVICE, 2021–2026 (USD MILLION)
TABLE 95 NORTH AMERICA: MARKET, BY DEPLOYMENT MODE, 2017–2020 (USD MILLION)
TABLE 96 NORTH AMERICA: MARKET, BY DEPLOYMENT MODE, 2021–2026 (USD MILLION)
TABLE 97 NORTH AMERICA: MARKET, BY ORGANIZATION SIZE, 2017–2020 (USD MILLION)
TABLE 98 NORTH AMERICA: NLP IN HEALTHCARE AND LIFE SCIENCES MARKET, BY ORGANIZATION SIZE, 2021–2026 (USD MILLION)
TABLE 99 NORTH AMERICA: MARKET, BY NLP TYPE, 2017–2020 (USD MILLION)
TABLE 100 NORTH AMERICA: MARKET, BY NLP TYPE, 2021–2026 (USD MILLION)
TABLE 101 NORTH AMERICA: MARKET, BY END USER, 2017–2020 (USD MILLION)
TABLE 102 NORTH AMERICA: MARKET, BY END USER, 2021–2026 (USD MILLION)
TABLE 103 NORTH AMERICA: MARKET, BY APPLICATION, 2017–2020 (USD MILLION)
TABLE 104 NORTH AMERICA: MARKET, BY APPLICATION, 2021–2026 (USD MILLION)
TABLE 105 NORTH AMERICA: MARKET, BY COUNTRY, 2017–2020 (USD MILLION)
TABLE 106 NORTH AMERICA: MARKET, BY COUNTRY, 2021–2026 (USD MILLION)
12.2.3 UNITED STATES
12.2.3.1 Rapid adoption and use of innovative solutions to gain insights from clinical data driving market growth in the US
TABLE 107 UNITED STATES: NLP IN HEALTHCARE AND LIFE SCIENCES MARKET, BY COMPONENT, 2017–2020 (USD MILLION)
TABLE 108 UNITED STATES: MARKET, BY COMPONENT, 2021–2026 (USD MILLION)
TABLE 109 UNITED STATES: MARKET, BY SOLUTION, 2017–2020 (USD MILLION)
TABLE 110 UNITED STATES: MARKET, BY SOLUTION, 2021–2026 (USD MILLION)
TABLE 111 UNITED STATES: MARKET, BY SERVICE, 2017–2020 (USD MILLION)
TABLE 112 UNITED STATES: MARKET, BY SERVICE, 2021–2026 (USD MILLION)
TABLE 113 UNITED STATES: MARKET, BY PROFESSIONAL SERVICE, 2017–2020 (USD MILLION)
TABLE 114 UNITED STATES: MARKET, BY PROFESSIONAL SERVICE, 2021–2026 (USD MILLION)
TABLE 115 UNITED STATES: MARKET, BY DEPLOYMENT MODE, 2017–2020 (USD MILLION)
TABLE 116 UNITED STATES: MARKET, BY DEPLOYMENT MODE, 2021–2026 (USD MILLION)
TABLE 117 UNITED STATES: NLP IN HEALTHCARE AND LIFE SCIENCES MARKET, BY ORGANIZATION SIZE, 2017–2020 (USD MILLION)
TABLE 118 UNITED STATES: MARKET, BY ORGANIZATION SIZE, 2021–2026 (USD MILLION)
TABLE 119 UNITED STATES: MARKET, BY NLP TYPE, 2017–2020 (USD MILLION)
TABLE 120 UNITED STATES: MARKET, BY NLP TYPE, 2021–2026 (USD MILLION)
TABLE 121 UNITED STATES: MARKET, BY END USER, 2017–2020 (USD MILLION)
TABLE 122 UNITED STATES: MARKET, BY END USER, 2021–2026 (USD MILLION)
TABLE 123 UNITED STATES: MARKET, BY APPLICATION, 2017–2020 (USD MILLION)
TABLE 124 UNITED STATES: MARKET, BY APPLICATION, 2021–2026 (USD MILLION)
12.2.4 CANADA
12.2.4.1 Favorable startup ecosystem to drive market growth in Canada
TABLE 125 CANADA: NLP IN HEALTHCARE AND LIFE SCIENCES MARKET, BY COMPONENT, 2017–2020 (USD MILLION)
TABLE 126 CANADA: MARKET, BY COMPONENT, 2021–2026 (USD MILLION)
TABLE 127 CANADA: MARKET, BY SOLUTION, 2017–2020 (USD MILLION)
TABLE 128 CANADA: MARKET, BY SOLUTION, 2021–2026 (USD MILLION)
TABLE 129 CANADA: MARKET, BY SERVICE, 2017–2020 (USD MILLION)
TABLE 130 CANADA: MARKET, BY SERVICE, 2021–2026 (USD MILLION)
TABLE 131 CANADA: MARKET, BY PROFESSIONAL SERVICE, 2017–2020 (USD MILLION)
TABLE 132 CANADA: MARKET, BY PROFESSIONAL SERVICE, 2021–2026 (USD MILLION)
TABLE 133 CANADA: MARKET, BY DEPLOYMENT MODE, 2017–2020 (USD MILLION)
TABLE 134 CANADA: MARKET, BY DEPLOYMENT MODE, 2021–2026 (USD MILLION)
TABLE 135 CANADA: MARKET, BY ORGANIZATION SIZE, 2017–2020 (USD MILLION)
TABLE 136 CANADA: NLP IN HEALTHCARE AND LIFE SCIENCES MARKET, BY ORGANIZATION SIZE, 2021–2026 (USD MILLION)
TABLE 137 CANADA: MARKET, BY NLP TYPE, 2017–2020 (USD MILLION)
TABLE 138 CANADA: MARKET, BY NLP TYPE, 2021–2026 (USD MILLION)
TABLE 139 CANADA: MARKET, BY END USER, 2017–2020 (USD MILLION)
TABLE 140 CANADA: MARKET, BY END USER, 2021–2026 (USD MILLION)
TABLE 141 CANADA: MARKET, BY APPLICATION, 2017–2020 (USD MILLION)
TABLE 142 CANADA: MARKET, BY APPLICATION, 2021–2026 (USD MILLION)
12.3 EUROPE
12.3.1 EUROPE: COVID-19 IMPACT
12.3.2 EUROPE: REGULATIONS
12.3.2.1 General Data Protection Regulation
12.3.2.2 European Committee for Standardization
12.3.2.3 European Technical Standards Institute
12.3.2.4 European Centre for Disease Prevention and Control
12.3.2.5 European Federation of Pharmaceutical Industries and Associations
TABLE 143 EUROPE: NLP IN HEALTHCARE AND LIFE SCIENCES MARKET, BY COMPONENT, 2017–2020 (USD MILLION)
TABLE 144 EUROPE: MARKET, BY COMPONENT, 2021–2026 (USD MILLION)
TABLE 145 EUROPE: MARKET, BY SOLUTION, 2017–2020 (USD MILLION)
TABLE 146 EUROPE: MARKET, BY SOLUTION, 2021–2026 (USD MILLION)
TABLE 147 EUROPE: MARKET, BY SERVICE, 2017–2020 (USD MILLION)
TABLE 148 EUROPE: MARKET, BY SERVICE, 2021–2026 (USD MILLION)
TABLE 149 EUROPE: MARKET, BY PROFESSIONAL SERVICE, 2017–2020 (USD MILLION)
TABLE 150 EUROPE: MARKET, BY PROFESSIONAL SERVICE, 2021–2026 (USD MILLION)
TABLE 151 EUROPE: MARKET, BY DEPLOYMENT MODE, 2017–2020 (USD MILLION)
TABLE 152 EUROPE: NLP IN HEALTHCARE AND LIFE SCIENCES MARKET, BY DEPLOYMENT MODE, 2021–2026 (USD MILLION)
TABLE 153 EUROPE: MARKET, BY ORGANIZATION SIZE, 2017–2020 (USD MILLION)
TABLE 154 EUROPE: MARKET, BY ORGANIZATION SIZE, 2021–2026 (USD MILLION)
TABLE 155 EUROPE: MARKET, BY NLP TYPE, 2017–2020 (USD MILLION)
TABLE 156 EUROPE: MARKET, BY NLP TYPE, 2021–2026 (USD MILLION)
TABLE 157 EUROPE: MARKET, BY END USER, 2017–2020 (USD MILLION)
TABLE 158 EUROPE: MARKET, BY END USER, 2021–2026 (USD MILLION)
TABLE 159 EUROPE: MARKET, BY APPLICATION, 2017–2020 (USD MILLION)
TABLE 160 EUROPE: MARKET, BY APPLICATION, 2021–2026 (USD MILLION)
TABLE 161 EUROPE: MARKET, BY COUNTRY, 2017–2020 (USD MILLION)
TABLE 162 EUROPE: MARKET, BY COUNTRY, 2021–2026 (USD MILLION)
12.3.3 UNITED KINGDOM
12.3.3.1 Increasing usage of online platforms to help healthcare companies efficiently manage patient queries to drive the adoption of NLP solutions and services
TABLE 163 UNITED KINGDOM: NLP IN HEALTHCARE AND LIFE SCIENCES MARKET, BY COMPONENT, 2017–2020 (USD MILLION)
TABLE 164 UNITED KINGDOM: MARKET, BY COMPONENT, 2021–2026 (USD MILLION)
TABLE 165 UNITED KINGDOM: MARKET, BY DEPLOYMENT MODE, 2017–2020 (USD MILLION)
TABLE 166 UNITED KINGDOM: MARKET, BY DEPLOYMENT MODE, 2021–2026 (USD MILLION)
TABLE 167 UNITED KINGDOM: MARKET, BY ORGANIZATION SIZE, 2017–2020 (USD MILLION)
TABLE 168 UNITED KINGDOM: MARKET, BY ORGANIZATION SIZE, 2021–2026 (USD MILLION)
12.3.4 GERMANY
12.3.4.1 Growing digital mobility and digital spending across the healthcare industry to drive the growth of the market in Germany
TABLE 169 GERMANY: NLP IN HEALTHCARE AND LIFE SCIENCES MARKET, BY COMPONENT, 2017–2020 (USD MILLION)
TABLE 170 GERMANY: MARKET, BY COMPONENT, 2021–2026 (USD MILLION)
TABLE 171 GERMANY: MARKET, BY DEPLOYMENT MODE, 2017–2020 (USD MILLION)
TABLE 172 GERMANY: MARKET, BY DEPLOYMENT MODE, 2021–2026 (USD MILLION)
TABLE 173 GERMANY: MARKET, BY ORGANIZATION SIZE, 2017–2020 (USD MILLION)
TABLE 174 GERMANY: MARKET, BY ORGANIZATION SIZE, 2021–2026 (USD MILLION)
12.3.5 FRANCE
12.3.5.1 Growing concerns of NLP vendors over managing clinical data across healthcare sectors due to the changing digital transformation to drive the demand for NLP solutions
TABLE 175 FRANCE: NLP IN HEALTHCARE AND LIFE SCIENCES MARKET, BY COMPONENT, 2017–2020 (USD MILLION)
TABLE 176 FRANCE: MARKET, BY COMPONENT, 2021–2026 (USD MILLION)
TABLE 177 FRANCE: MARKET, BY DEPLOYMENT MODE, 2017–2020 (USD MILLION)
TABLE 178 FRANCE: MARKET, BY DEPLOYMENT MODE, 2021–2026 (USD MILLION)
TABLE 179 FRANCE: MARKET, BY ORGANIZATION SIZE, 2017–2020 (USD MILLION)
TABLE 180 FRANCE: MARKET, BY ORGANIZATION SIZE, 2021–2026 (USD MILLION)
12.3.6 REST OF EUROPE
12.4 ASIA PACIFIC
12.4.1 ASIA PACIFIC: COVID-19 IMPACT
12.4.2 ASIA PACIFIC: REGULATIONS
12.4.2.1 Personal Data Protection Act
12.4.2.2 International Organization for Standardization 27001
12.4.2.3 Act on the Protection of Personal Information
12.4.2.4 Critical Information Infrastructure
FIGURE 50 ASIA PACIFIC: MARKET SNAPSHOT
TABLE 181 ASIA PACIFIC: NLP IN HEALTHCARE AND LIFE SCIENCES MARKET, BY COMPONENT, 2017–2020 (USD MILLION)
TABLE 182 ASIA PACIFIC: MARKET, BY COMPONENT, 2021–2026 (USD MILLION)
TABLE 183 ASIA PACIFIC: MARKET, BY SOLUTION, 2017–2020 (USD MILLION)
TABLE 184 ASIA PACIFIC: MARKET, BY SOLUTION, 2021–2026 (USD MILLION)
TABLE 185 ASIA PACIFIC: MARKET, BY SERVICE, 2017–2020 (USD MILLION)
TABLE 186 ASIA PACIFIC: MARKET, BY SERVICE, 2021–2026 (USD MILLION)
TABLE 187 ASIA PACIFIC: MARKET, BY PROFESSIONAL SERVICE, 2017–2020 (USD MILLION)
TABLE 188 ASIA PACIFIC: MARKET, BY PROFESSIONAL SERVICE, 2021–2026 (USD MILLION)
TABLE 189 ASIA PACIFIC: MARKET, BY DEPLOYMENT MODE, 2017–2020 (USD MILLION)
TABLE 190 ASIA PACIFIC: MARKET, BY DEPLOYMENT MODE, 2021–2026 (USD MILLION)
TABLE 191 ASIA PACIFIC: MARKET, BY ORGANIZATION SIZE, 2017–2020 (USD MILLION)
TABLE 192 ASIA PACIFIC: NLP IN HEALTHCARE AND LIFE SCIENCES MARKET, BY ORGANIZATION SIZE, 2021–2026 (USD MILLION)
TABLE 193 ASIA PACIFIC: MARKET, BY NLP TYPE, 2017–2020 (USD MILLION)
TABLE 194 ASIA PACIFIC: MARKET, BY NLP TYPE, 2021–2026 (USD MILLION)
TABLE 195 ASIA PACIFIC: MARKET, BY END USER, 2017–2020 (USD MILLION)
TABLE 196 ASIA PACIFIC: MARKET, BY END USER, 2021–2026 (USD MILLION)
TABLE 197 ASIA PACIFIC: MARKET, BY APPLICATION, 2017–2020 (USD MILLION)
TABLE 198 ASIA PACIFIC: MARKET, BY APPLICATION, 2021–2026 (USD MILLION)
TABLE 199 ASIA PACIFIC: MARKET, BY COUNTRY, 2017–2020 (USD MILLION)
TABLE 200 ASIA PACIFIC: MARKET, BY COUNTRY, 2021–2026 (USD MILLION)
12.4.3 CHINA
12.4.3.1 Growing need to effectively manage huge amounts of clinical data to boost the demand for NLP solutions in China
TABLE 201 CHINA: NLP IN HEALTHCARE AND LIFE SCIENCES MARKET, BY COMPONENT, 2017–2020 (USD MILLION)
TABLE 202 CHINA: MARKET, BY COMPONENT, 2021–2026 (USD MILLION)
TABLE 203 CHINA: MARKET, BY DEPLOYMENT MODE, 2017–2020 (USD MILLION)
TABLE 204 CHINA: MARKET, BY DEPLOYMENT MODE, 2021–2026 (USD MILLION)
TABLE 205 CHINA: MARKET, BY ORGANIZATION SIZE, 2017–2020 (USD MILLION)
TABLE 206 CHINA: MARKET, BY ORGANIZATION SIZE, 2021–2026 (USD MILLION)
12.4.4 JAPAN
12.4.4.1 Growing adoption of AI in healthcare organizations across Japan to drive market growth
TABLE 207 JAPAN: NLP IN HEALTHCARE AND LIFE SCIENCES MARKET, BY COMPONENT, 2017–2020 (USD MILLION)
TABLE 208 JAPAN: MARKET, BY COMPONENT, 2021–2026 (USD MILLION)
TABLE 209 JAPAN: MARKET, BY DEPLOYMENT MODE, 2017–2020 (USD MILLION)
TABLE 210 JAPAN: MARKET, BY DEPLOYMENT MODE, 2021–2026 (USD MILLION)
TABLE 211 JAPAN: MARKET, BY ORGANIZATION SIZE, 2017–2020 (USD MILLION)
TABLE 212 JAPAN: MARKET, BY ORGANIZATION SIZE, 2021–2026 (USD MILLION)
12.4.5 INDIA
12.4.5.1 Increasing government initiatives and innovative technologies to fuel the demand for NLP solutions in India
TABLE 213 INDIA: NLP IN HEALTHCARE AND LIFE SCIENCES MARKET, BY COMPONENT, 2017–2020 (USD MILLION)
TABLE 214 INDIA: MARKET, BY COMPONENT, 2021–2026 (USD MILLION)
TABLE 215 INDIA: MARKET, BY DEPLOYMENT MODE, 2017–2020 (USD MILLION)
TABLE 216 INDIA: MARKET, BY DEPLOYMENT MODE, 2021–2026 (USD MILLION)
TABLE 217 INDIA: MARKET, BY ORGANIZATION SIZE, 2017–2020 (USD MILLION)
TABLE 218 INDIA: MARKET, BY ORGANIZATION SIZE, 2021–2026 (USD MILLION)
12.4.6 REST OF ASIA PACIFIC
12.5 MIDDLE EAST AND AFRICA
12.5.1 MIDDLE EAST AND AFRICA: COVID-19 IMPACT
12.5.2 MIDDLE EAST AND AFRICA: REGULATIONS
12.5.2.1 UAE Ministry of Health (the Ministry)
12.5.2.2 Health Authority - Abu Dhabi
12.5.2.3 Dubai Health Authority
12.5.2.4 Federal Law No. 2 of 2019 (Health Data Law)
12.5.2.5 Israeli Privacy Protection Regulations (Data Security), 5777-2017
12.5.2.6 Applicability of the GDPR in companies from the KSA
12.5.2.7 Protection of Personal Information Act
TABLE 219 MIDDLE EAST AND AFRICA: NLP IN HEALTHCARE AND LIFE SCIENCES MARKET, BY COMPONENT, 2017–2020 (USD MILLION)
TABLE 220 MIDDLE EAST AND AFRICA: MARKET, BY COMPONENT, 2021–2026 (USD MILLION)
TABLE 221 MIDDLE EAST AND AFRICA: MARKET, BY SOLUTION, 2017–2020 (USD MILLION)
TABLE 222 MIDDLE EAST AND AFRICA: MARKET, BY SOLUTION, 2021–2026 (USD MILLION)
TABLE 223 MIDDLE EAST AND AFRICA: MARKET, BY SERVICE, 2017–2020 (USD MILLION)
TABLE 224 MIDDLE EAST AND AFRICA: MARKET, BY SERVICE, 2021–2026 (USD MILLION)
TABLE 225 MIDDLE EAST AND AFRICA: MARKET, BY PROFESSIONAL SERVICE, 2017–2020 (USD MILLION)
TABLE 226 MIDDLE EAST AND AFRICA: MARKET, BY PROFESSIONAL SERVICE, 2021–2026 (USD MILLION)
TABLE 227 MIDDLE EAST AND AFRICA: MARKET, BY DEPLOYMENT MODE, 2017–2020 (USD MILLION)
TABLE 228 MIDDLE EAST AND AFRICA: NLP IN HEALTHCARE AND LIFE SCIENCES MARKET, BY DEPLOYMENT MODE, 2021–2026 (USD MILLION)
TABLE 229 MIDDLE EAST AND AFRICA: MARKET, BY ORGANIZATION SIZE, 2017–2020 (USD MILLION)
TABLE 230 MIDDLE EAST AND AFRICA: MARKET, BY ORGANIZATION SIZE, 2021–2026 (USD MILLION)
TABLE 231 MIDDLE EAST AND AFRICA: MARKET, BY NLP TYPE, 2017–2020 (USD MILLION)
TABLE 232 MIDDLE EAST AND AFRICA: MARKET, BY NLP TYPE, 2021–2026 (USD MILLION)
TABLE 233 MIDDLE EAST AND AFRICA: MARKET, BY END USER, 2017–2020 (USD MILLION)
TABLE 234 MIDDLE EAST AND AFRICA: MARKET, BY END USER, 2021–2026 (USD MILLION)
TABLE 235 MIDDLE EAST AND AFRICA: MARKET, BY APPLICATION, 2017–2020 (USD MILLION)
TABLE 236 MIDDLE EAST AND AFRICA: MARKET, BY APPLICATION, 2021–2026 (USD MILLION)
TABLE 237 MIDDLE EAST AND AFRICA: MARKET, BY COUNTRY, 2017–2020 (USD MILLION)
TABLE 238 MIDDLE EAST AND AFRICA: MARKET, BY COUNTRY, 2021–2026 (USD MILLION)
12.5.3 KINGDOM OF SAUDI ARABIA
12.5.3.1 Increasing initiatives taken by the KSA government and private sectors for technological adoption to drive market growth in the KSA
TABLE 239 KINGDOM OF SAUDI ARABIA: NLP IN HEALTHCARE AND LIFE SCIENCES MARKET, BY COMPONENT, 2017–2020 (USD MILLION)
TABLE 240 KINGDOM OF SAUDI ARABIA: MARKET, BY COMPONENT, 2021–2026 (USD MILLION)
TABLE 241 KINGDOM OF SAUDI ARABIA: MARKET, BY DEPLOYMENT MODE, 2017–2020 (USD MILLION)
TABLE 242 KINGDOM OF SAUDI ARABIA: MARKET, BY DEPLOYMENT MODE, 2021–2026 (USD MILLION)
TABLE 243 KINGDOM OF SAUDI ARABIA: MARKET, BY ORGANIZATION SIZE, 2017–2020 (USD MILLION)
TABLE 244 KINGDOM OF SAUDI ARABIA: MARKET, BY ORGANIZATION SIZE, 2021–2026 (USD MILLION)
12.5.4 UNITED ARAB EMIRATES
12.5.4.1 Growing investments in AI tools and technologies in the healthcare sector support market growth in the UAE
TABLE 245 UNITED ARAB EMIRATES: NLP IN HEALTHCARE AND LIFE SCIENCES MARKET, BY COMPONENT, 2017–2020 (USD MILLION)
TABLE 246 UNITED ARAB EMIRATES: MARKET, BY COMPONENT, 2021–2026 (USD MILLION)
TABLE 247 UNITED ARAB EMIRATES: MARKET, BY DEPLOYMENT MODE, 2017–2020 (USD MILLION)
TABLE 248 UNITED ARAB EMIRATES: MARKET, BY DEPLOYMENT MODE, 2021–2026 (USD MILLION)
TABLE 249 UNITED ARAB EMIRATES: MARKET, BY ORGANIZATION SIZE, 2017–2020 (USD MILLION)
TABLE 250 UNITED ARAB EMIRATES: MARKET, BY ORGANIZATION SIZE, 2021–2026 (USD MILLION)
12.5.5 SOUTH AFRICA
12.5.5.1 Growing digitalization in African countries offers opportunities for the NLP in healthcare and life sciences market in Africa
TABLE 251 SOUTH AFRICA: MARKET, BY COMPONENT, 2017–2020 (USD MILLION)
TABLE 252 SOUTH AFRICA: MARKET, BY COMPONENT, 2021–2026 (USD MILLION)
TABLE 253 SOUTH AFRICA: MARKET, BY DEPLOYMENT MODE, 2017–2020 (USD MILLION)
TABLE 254 SOUTH AFRICA: MARKET, BY DEPLOYMENT MODE, 2021–2026 (USD MILLION)
TABLE 255 SOUTH AFRICA: MARKET, BY ORGANIZATION SIZE, 2017–2020 (USD MILLION)
TABLE 256 SOUTH AFRICA: MARKET, BY ORGANIZATION SIZE, 2021–2026 (USD MILLION)
12.5.6 REST OF MIDDLE EAST AND AFRICA
12.6 LATIN AMERICA
12.6.1 LATIN AMERICA: COVID-19 IMPACT
12.6.2 LATIN AMERICA: REGULATIONS
12.6.2.1 General Health Law
12.6.2.2 ANVISA - Brazil National Health Surveillance Agency
12.6.2.3 Brazil Data Protection Law
12.6.2.4 Argentina Personal Data Protection Law No. 25.326
TABLE 257 LATIN AMERICA: NLP IN HEALTHCARE AND LIFE SCIENCES MARKET, BY COMPONENT, 2017–2020 (USD MILLION)
TABLE 258 LATIN AMERICA: MARKET, BY COMPONENT, 2021–2026 (USD MILLION)
TABLE 259 LATIN AMERICA: MARKET, BY SOLUTION, 2017–2020 (USD MILLION)
TABLE 260 LATIN AMERICA: MARKET, BY SOLUTION, 2021–2026 (USD MILLION)
TABLE 261 LATIN AMERICA: MARKET, BY SERVICE, 2017–2020 (USD MILLION)
TABLE 262 LATIN AMERICA: MARKET, BY SERVICE, 2021–2026 (USD MILLION)
TABLE 263 LATIN AMERICA: MARKET, BY PROFESSIONAL SERVICE, 2017–2020 (USD MILLION)
TABLE 264 LATIN AMERICA: MARKET, BY PROFESSIONAL SERVICE, 2021–2026 (USD MILLION)
TABLE 265 LATIN AMERICA: MARKET, BY DEPLOYMENT MODE, 2017–2020 (USD MILLION)
TABLE 266 LATIN AMERICA: MARKET, BY DEPLOYMENT MODE, 2021–2026 (USD MILLION)
TABLE 267 LATIN AMERICA: MARKET, BY ORGANIZATION SIZE, 2017–2020 (USD MILLION)
TABLE 268 LATIN AMERICA: NLP IN HEALTHCARE AND LIFE SCIENCES MARKET, BY ORGANIZATION SIZE, 2021–2026 (USD MILLION)
TABLE 269 LATIN AMERICA: MARKET, BY NLP TYPE, 2017–2020 (USD MILLION)
TABLE 270 LATIN AMERICA: MARKET, BY NLP TYPE, 2021–2026 (USD MILLION)
TABLE 271 LATIN AMERICA: MARKET, BY END USER, 2017–2020 (USD MILLION)
TABLE 272 LATIN AMERICA: MARKET, BY END USER, 2021–2026 (USD MILLION)
TABLE 273 LATIN AMERICA: MARKET, BY APPLICATION, 2017–2020 (USD MILLION)
TABLE 274 LATIN AMERICA: MARKET, BY APPLICATION, 2021–2026 (USD MILLION)
TABLE 275 LATIN AMERICA: MARKET, BY COUNTRY, 2017–2020 (USD MILLION)
TABLE 276 LATIN AMERICA: MARKET, BY COUNTRY, 2021–2026 (USD MILLION)
12.6.3 BRAZIL
12.6.3.1 Increased number of healthcare regulatory bodies promotes investment and penetration in the country
TABLE 277 BRAZIL: NLP IN HEALTHCARE AND LIFE SCIENCES MARKET, BY COMPONENT, 2017–2020 (USD MILLION)
TABLE 278 BRAZIL: MARKET, BY COMPONENT, 2021–2026 (USD MILLION)
TABLE 279 BRAZIL: MARKET, BY DEPLOYMENT MODE, 2017–2020 (USD MILLION)
TABLE 280 BRAZIL: MARKET, BY DEPLOYMENT MODE, 2021–2026 (USD MILLION)
TABLE 281 BRAZIL: MARKET, BY ORGANIZATION SIZE, 2017–2020 (USD MILLION)
TABLE 282 BRAZIL: MARKET, BY ORGANIZATION SIZE, 2021–2026 (USD MILLION)
12.6.4 MEXICO
12.6.4.1 Development of new technology policies and increasing AI investments are boosting the market growth in the country
TABLE 283 MEXICO: NLP IN HEALTHCARE AND LIFE SCIENCES MARKET, BY COMPONENT, 2017–2020 (USD MILLION)
TABLE 284 MEXICO: MARKET, BY COMPONENT, 2021–2026 (USD MILLION)
TABLE 285 MEXICO: MARKET, BY DEPLOYMENT MODE, 2017–2020 (USD MILLION)
TABLE 286 MEXICO: MARKET, BY DEPLOYMENT MODE, 2021–2026 (USD MILLION)
TABLE 287 MEXICO: MARKET, BY ORGANIZATION SIZE, 2017–2020 (USD MILLION)
TABLE 288 MEXICO: MARKET, BY ORGANIZATION SIZE, 2021–2026 (USD MILLION)
12.6.5 REST OF LATIN AMERICA
13 COMPETITIVE LANDSCAPE (Page No. - 237)
13.1 OVERVIEW
13.2 KEY PLAYER STRATEGIES
13.3 REVENUE ANALYSIS
FIGURE 51 REVENUE ANALYSIS FOR KEY COMPANIES IN THE PAST FIVE YEARS
13.4 MARKET SHARE ANALYSIS
TABLE 289 NLP IN HEALTHCARE AND LIFE SCIENCES MARKET: DEGREE OF COMPETITION
13.5 COMPANY EVALUATION QUADRANT
13.5.1 STARS
13.5.2 EMERGING LEADERS
13.5.3 PERVASIVE
13.5.4 PARTICIPANT
FIGURE 52 KEY MARKET PLAYERS, COMPANY EVALUATION MATRIX, 2021
13.6 COMPETITIVE BENCHMARKING
13.6.1 COMPANY PRODUCT FOOTPRINT
FIGURE 53 PRODUCT PORTFOLIO ANALYSIS OF TOP PLAYERS IN THE MARKET
FIGURE 54 BUSINESS STRATEGY EXCELLENCE OF TOP PLAYERS IN THE NLP IN HEALTHCARE AND LIFE SCIENCES MARKET
TABLE 290 COMPANY OFFERING FOOTPRINT
TABLE 291 COMPANY REGION FOOTPRINT
13.7 STARTUP/SME EVALUATION QUADRANT
13.7.1 PROGRESSIVE COMPANIES
13.7.2 RESPONSIVE COMPANIES
13.7.3 DYNAMIC COMPANIES
13.7.4 STARTING BLOCKS
FIGURE 55 STARTUP/SME NLP IN HEALTHCARE AND LIFE SCIENCES MARKET EVALUATION MATRIX, 2021
13.8 STARTUP/SME COMPETITIVE BENCHMARKING
13.8.1 COMPANY PRODUCT FOOTPRINT
FIGURE 56 PRODUCT PORTFOLIO ANALYSIS OF STARTUP/SME IN THE MARKET
FIGURE 57 BUSINESS STRATEGY EXCELLENCE OF STARTUP/SME IN THE MARKET
TABLE 292 STARTUP/SME COMPANY OFFERING FOOTPRINT
TABLE 293 STARTUP/SME COMPANY REGION FOOTPRINT
13.9 COMPETITIVE SCENARIO AND TRENDS
13.9.1 PRODUCT LAUNCHES
TABLE 294 NLP IN HEALTHCARE AND LIFE SCIENCES MARKET: PRODUCT LAUNCHES, JANUARY 2018–MAY 2021
13.9.2 DEALS
TABLE 295 MARKET: DEALS, JANUARY 2018– MAY 2021
13.9.3 OTHERS
TABLE 296 MARKET: OTHERS, JANUARY 2018– MAY 2021
14 COMPANY PROFILES (Page No. - 252)
14.1 INTRODUCTION
(Business and financial Overview, Solutions Offered, Recent Developments, MnM View, Key strengths/Right to Win, Strategic Choices Made, and Weaknesses and Competitive Threats)*
14.2 KEY PLAYERS
14.2.1 IBM
TABLE 297 IBM: BUSINESS OVERVIEW
FIGURE 58 IBM: COMPANY SNAPSHOT
TABLE 298 IBM: SOLUTIONS OFFERED
TABLE 299 IBM: PRODUCT LAUNCHES AND ENHANCEMENTS
TABLE 300 IBM: DEALS
14.2.2 GOOGLE
TABLE 301 GOOGLE: BUSINESS AND FINANCIAL OVERVIEW
FIGURE 59 GOOGLE: COMPANY SNAPSHOT
TABLE 302 GOOGLE: PRODUCT/SOLUTION/SERVICE OFFERED
TABLE 303 GOOGLE: PRODUCT LAUNCHES AND ENHANCEMENTS
TABLE 304 GOOGLE: DEALS
14.2.3 MICROSOFT
TABLE 305 MICROSOFT: BUSINESS OVERVIEW
FIGURE 60 MICROSOFT: COMPANY SNAPSHOT
TABLE 306 MICROSOFT: SOLUTIONS OFFERED
TABLE 307 MICROSOFT: PRODUCT LAUNCHES AND ENHANCEMENTS
TABLE 308 MICROSOFT: DEALS
14.2.4 3M
TABLE 309 3M: BUSINESS OVERVIEW
FIGURE 61 3M: COMPANY SNAPSHOT
TABLE 310 3M: SOLUTIONS OFFERED
TABLE 311 3M: PRODUCT LAUNCHES AND ENHANCEMENTS
TABLE 312 3M: DEALS
14.2.5 CERNER
TABLE 313 CERNER: BUSINESS OVERVIEW
FIGURE 62 CERNER: COMPANY SNAPSHOT
TABLE 314 CERNER: SOLUTIONS OFFERED
TABLE 315 CERNER: PRODUCT LAUNCHES AND ENHANCEMENTS
TABLE 316 CERNER: DEALS
14.2.6 AWS
TABLE 317 AWS: BUSINESS OVERVIEW
FIGURE 63 AWS: COMPANY SNAPSHOT
TABLE 318 AWS: SERVICE OFFERED
TABLE 319 AWS: PRODUCT LAUNCHES AND ENHANCEMENTS
TABLE 320 AWS: OTHERS
14.2.7 INOVALON
TABLE 321 INOVALON: BUSINESS OVERVIEW
FIGURE 64 INOVALON: COMPANY SNAPSHOT
TABLE 322 INOVALON: SOLUTIONS OFFERED
TABLE 323 INOVALON: PRODUCT LAUNCHES AND ENHANCEMENTS
TABLE 324 INOVALON: DEALS
14.2.8 DOLBEY
TABLE 325 DOLBEY: BUSINESS OVERVIEW
TABLE 326 DOLBEY: SOLUTIONS OFFERED
TABLE 327 DOLBEY: DEALS
14.2.9 AVERBIS
TABLE 328 AVERBIS: BUSINESS OVERVIEW
TABLE 329 AVERBIS: SOLUTIONS OFFERED
TABLE 330 AVERBIS: PRODUCT LAUNCHES AND ENHANCEMENTS
14.2.10 LINGUAMATICS
TABLE 331 LINGUAMATICS: BUSINESS OVERVIEW
TABLE 332 LINGUAMATICS: SOLUTIONS OFFERED
TABLE 333 LINGUAMATICS: PRODUCT LAUNCHES AND ENHANCEMENTS
TABLE 334 LINGUAMATICS: DEALS
14.2.11 APIXIO
14.2.12 CLINITHINK
14.2.13 LEXALYTICS
14.2.14 HEALTH FIDELITY
14.2.15 FLATIRON
14.2.16 CAPTION HEALTH
14.2.17 BABYLON
14.3 SMES/START UPS
14.3.1 FORESEE MEDICAL
14.3.2 PRESS GANEY
14.3.3 GNANI.AI
14.3.4 NOTABLE
14.3.5 BIOFOURMIS
14.3.6 SUKI
14.3.7 WAVE HEALTH TECHNOLOGIES
14.3.8 CORTI
14.3.9 CLOUDMEDX
14.3.10 ONCORA MEDICAL
*Details on Business and financial Overview, Solutions Offered, Recent Developments, MnM View, Key strengths/Right to Win, Strategic Choices Made, and Weaknesses and Competitive Threats might not be captured in case of unlisted companies.
15 ADJACENT AND RELATED MARKETS (Page No. - 294)
15.1 INTRODUCTION
15.2 NATURAL LANGUAGE PROCESSING MARKET - GLOBAL FORECAST TO 2026
15.2.1 MARKET DEFINITION
15.2.2 MARKET OVERVIEW
TABLE 335 GLOBAL NATURAL LANGUAGE PROCESSING MARKET SIZE AND GROWTH RATE, 2015–2019 (USD MILLION, Y-O-Y %)
TABLE 336 GLOBAL NATURAL LANGUAGE PROCESSING MARKET SIZE AND GROWTH RATE, 2019–2026 (USD MILLION, Y-O-Y %)
15.2.2.1 NLP market, by component
TABLE 337 NATURAL LANGUAGE PROCESSING MARKET SIZE, BY COMPONENT, 2015–2019 (USD MILLION)
TABLE 338 NATURAL LANGUAGE PROCESSING MARKET SIZE, BY COMPONENT, 2019–2026 (USD MILLION)
15.2.2.2 NLP market, by deployment mode
TABLE 339 NATURAL LANGUAGE PROCESSING MARKET SIZE, BY DEPLOYMENT MODE, 2015–2019 (USD MILLION)
TABLE 340 NATURAL LANGUAGE PROCESSING MARKET SIZE, BY DEPLOYMENT MODE, 2019–2026 (USD MILLION)
15.2.2.3 NLP market, by organization size
TABLE 341 NATURAL LANGUAGE PROCESSING MARKET SIZE, BY ORGANIZATION SIZE, 2015–2019 (USD MILLION)
TABLE 342 NATURAL LANGUAGE PROCESSING MARKET SIZE, BY ORGANIZATION SIZE, 2019–2026 (USD MILLION)
15.2.2.4 NLP market, by type
TABLE 343 NATURAL LANGUAGE PROCESSING MARKET SIZE, BY TYPE, 2015–2019 (USD MILLION)
TABLE 344 NATURAL LANGUAGE PROCESSING MARKET SIZE, BY TYPE, 2019–2026 (USD MILLION)
15.2.2.5 NLP market, by region
TABLE 345 NATURAL LANGUAGE PROCESSING MARKET SIZE, BY REGION, 2015–2019 (USD MILLION)
TABLE 346 NATURAL LANGUAGE PROCESSING MARKET SIZE, BY REGION, 2019–2026 (USD MILLION)
15.3 MOBILE APPS AND WEB ANALYTICS MARKET - GLOBAL FORECAST TO 2025
15.3.1 MARKET DEFINITION
15.3.2 MARKET OVERVIEW
TABLE 347 MOBILE APPS AND WEB ANALYTICS MARKET SIZE AND GROWTH RATE, 2015–2019 (USD MILLION, Y-O-Y %)
TABLE 348 MOBILE APPS AND WEB ANALYTICS MARKET SIZE AND GROWTH RATE, 2019–2025 (USD MILLION, Y-O-Y %)
15.3.2.1 Mobile apps and web analytics market, by component
TABLE 349 MOBILE APPS AND WEB ANALYTICS MARKET SIZE, BY COMPONENT, 2016–2019 (USD MILLION)
TABLE 350 MOBILE APPS AND WEB ANALYTICS MARKET SIZE, BY COMPONENT, 2019–2025 (USD MILLION)
15.3.2.2 Mobile apps and web analytics market, by application
TABLE 351 MOBILE APPS AND WEB ANALYTICS MARKET SIZE, BY APPLICATION, 2016–2019 (USD MILLION)
TABLE 352 MOBILE APPS AND WEB ANALYTICS MARKET SIZE, BY APPLICATION, 2019–2025 (USD MILLION)
15.3.2.3 Mobile apps and web analytics market, by deployment mode
TABLE 353 MOBILE APPS AND WEB ANALYTICS MARKET SIZE, BY DEPLOYMENT MODE, 2016–2019 (USD MILLION)
TABLE 354 MOBILE APPS AND WEB ANALYTICS MARKET SIZE, BY DEPLOYMENT MODE, 2019–2025 (USD MILLION)
15.3.2.4 Mobile apps and web analytics market, by organization size
TABLE 355 MOBILE APPS AND WEB ANALYTICS MARKET SIZE, BY ORGANIZATION SIZE, 2016–2019 (USD MILLION)
TABLE 356 MOBILE APPS AND WEB ANALYTICS MARKET SIZE, BY ORGANIZATION SIZE, 2019–2025 (USD MILLION)
15.3.2.5 Mobile apps and web analytics market, by industry vertical
TABLE 357 MOBILE APPS AND WEB ANALYTICS MARKET SIZE, BY INDUSTRY VERTICAL, 2016–2019 (USD MILLION)
TABLE 358 MOBILE APPS AND WEB ANALYTICS MARKET SIZE, BY INDUSTRY VERTICAL, 2019–2025 (USD MILLION)
15.3.2.6 Mobile apps and web analytics market, by region
TABLE 359 MOBILE APPS AND WEB ANALYTICS MARKET SIZE, BY REGION, 2016–2019 (USD MILLION)
TABLE 360 MOBILE APPS AND WEB ANALYTICS MARKET SIZE, BY REGION, 2019–2025 (USD MILLION)
16 APPENDIX (Page No. - 307)
16.1 INDUSTRY EXPERTS
16.2 DISCUSSION GUIDE
16.3 KNOWLEDGE STORE: MARKETSANDMARKETS’ SUBSCRIPTION PORTAL
16.4 AVAILABLE CUSTOMIZATIONS
16.5 RELATED REPORTS
16.6 AUTHOR DETAILS
The study involved four major activities in estimating the current market size of the NLP in healthcare and life sciences market. Extensive secondary research was done to collect information on the market, peer market, and parent market. The next step was to validate these findings, assumptions, and sizing with industry experts across the value chain through primary research. Both top-down and bottom-up approaches were used to estimate the total market size. After that, the market breakup and data triangulation procedures were used to estimate the market size of the segments and subsegments of the marine software market.
Secondary Research
In the secondary research process, various sources were referred to for identifying and collecting information for the study. The secondary sources included annual reports, press releases, investor presentations of companies; white papers; journals; and certified publications and articles from recognized authors, directories, and databases.
Primary Research
Various primary sources from both supply and demand sides were interviewed to obtain qualitative and quantitative information on the market. The primary sources from the supply side included various industry experts, including Chief X Officers (CXOs); Vice Presidents (VPs); directors from business development, marketing, and product development/innovation teams; related key executives from NLP software vendors, system integrators, healthcare professionals, healthcare workers, professional service providers, industry associations, and consultants; and key opinion leaders. All possible parameters that affect the market covered in this research study have been accounted for, viewed in extensive detail, verified through primary research, and analyzed to get the final quantitative and qualitative data.
The following is the breakup of primary profiles:
To know about the assumptions considered for the study, download the pdf brochure
Market Size Estimation
Both top-down and bottom-up approaches were used to estimate and validate the total size of the NLP in healthcare and life sciences market. The top-down approach was used to derive the revenue contribution of top vendors and their offerings in the market. The bottom-up approach was used to arrive at the overall market size of the global NLP in healthcare and life sciences market using key companies’ revenue and their offerings in the market. The research methodology used to estimate the market size includes the following:
- The key players in the market were identified through extensive secondary research.
- The market size, in terms of value, was determined through primary and secondary research processes.
- All percentages, shares, and breakups were determined using secondary sources and verified through primary sources.
Data Triangulation
After arriving at the overall market size using the market size estimation processes as explained above, the market was split into several segments and subsegments. To complete the overall market engineering process and arrive at the exact statistics of each market segment and subsegment, data triangulation, and market breakup procedures were employed, wherever applicable. The overall market size was then used in the top-down procedure to estimate the size of other individual markets via percentage splits of the market segmentation.
Report Objectives
- To define, describe, and predict the NLP in healthcare and life sciences market by component (solutions and services), NLP Type, application, deployment mode, organization size, end user, and region
- To provide detailed information related to major factors (drivers, restraints, opportunities, and industry-specific challenges) influencing the market growth
- To analyze opportunities in the market and provide details of the competitive landscape for stakeholders and market leaders
- To forecast the market size of segments for five main regions: North America, Europe, Asia Pacific (APAC), Middle East and Africa (MEA), and Latin America
- To profile key players and comprehensively analyze their market rankings and core competencies
- To analyze competitive developments, such as partnerships, new product launches, and mergers and acquisitions, in the market
- To analyze the impact of the COVID-19 pandemic on the NLP in healthcare and life sciences market
Available Customizations
With the given market data, MarketsandMarkets offers customizations as per the company’s specific needs. The following customization options are available for the report:
Product analysis
- Product matrix provides a detailed comparison of the product portfolio of each company
Geographic analysis
- Further breakup of the North American NLP in healthcare and life sciences market
- Further breakup of the European market
- Further breakup of the APAC market
- Further breakup of the Latin American market
- Further breakup of the MEA market
Company information
- Detailed analysis and profiling of additional market players up to 5
- Triangulate with your Own Data
- Get Data as per your Format and Definition
- Gain a Deeper Dive on a Specific Application, Geography, Customer or Competitor
- Any level of Personalization
- What are the Known and Unknown Adjacencies Impacting the NLP in Healthcare and Life Sciences Market
- What will your New Revenue Sources be?
- Who will be your Top Customer; what will make them switch?
- Defend your Market Share or Win Competitors
- Get a Scorecard for Target Partners
Growth opportunities and latent adjacency in NLP in Healthcare and Life Sciences Market
Understand the application of NLP in Healthcare.
Gather insights into Natural Language Processing, Automatic Speech Recognition in Healthcare, Computational Lexicography, Dictionaries, Terminologies.
Detailed understanding of the Artificial Intelligence (Data Scientist, Machine Learning, NLP, Sentiment Analysis, Recommender Systems).