Artificial Intelligence in Healthcare Market

Artificial Intelligence in Healthcare Market by Offering (Hardware, Software, Services), Technology (Machine Learning, NLP, Context-Aware Computing, Computer Vision), End-Use Application, End User, and Geography – Global Forecast to 2025

Report Code: SE 5225 Dec, 2018, by marketsandmarkets.com
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MarketsandMarkets forecasts the artificial intelligence in healthcare market to be valued at USD 2.10 billion in 2018 and is likely to reach USD 36.15 billion by 2025, at a CAGR of 50.2% during the forecast period. Major drivers for the market are increasingly large and complex data set driving the need for AI; growing demand to reduce the increasing healthcare costs; improving computing power and declining hardware cost; growing number of cross-industry partnerships and collaborations; and increasing imbalance between health workforce and patients driving the need for improvised healthcare services.

Artificial Intelligence in Healthcare Market

By offering, services to grow at highest CAGR during forecast period

Growing adoption of AI in hospitals and other healthcare service providers is expected to boost the demand for services segment in later part of the forecast period.

By technology, the artificial intelligence in healthcare market for Machine learning technology to hold the largest market share throughout the forecast period

Machine learning’s ability to collect and handle big data, and its applications in various healthcare applications, such as patient data and risk analysis, drug discovery, and in-patient care and hospital management, are fueling its growth.

Artificial Intelligence in Healthcare Market

By geography, North America is expected to dominate the healthcare market

The North American AI in healthcare market is further segmented into the US, Canada, and Mexico. The US is considered one of the major contributors in the North American AI in healthcare market. The US is one of the leading countries in the world to adopt AI technology across the continuum of care.

Cross-industry participation in the healthcare domain along with significant increase in venture capital investment, is encouraging several new players to enter the market for AI in the healthcare space.

Market Dynamics

Driver: Rising need for improvised healthcare services due to imbalance between health workforce and patients

Maintaining a balance between health workforce and patients is a challenge in developed and developing countries, including the US, the UK, Germany, and India. AI and cognitive mobility platforms are helping medical practitioners easily and efficiently achieve their tasks with minimal human intervention. The deep learning technology in medical imaging solutions helps in various pathology tests, such as blood test, X-ray analysis, and cancer cell detection. The patient engagement

AI systems assist in medication management with the help of NLP and context aware processing technology. Therefore, with the decrease in doctor–patient ratio, AI brings in new solutions to bridge the gap between health workforce and patients.

Restraint: Reluctance among medical practitioners to adopt AI-based technologies

AI technologies offer doctors with tools that help them in better diagnose and effectively treat patients. However, there is an observed reluctance among doctors with regard to new technologies. For instance, there is a misconception among medical practitioners that AI will replace doctors in the coming years. Currently, many healthcare professionals have doubts over the capabilities of AI solutions in terms of accurately diagnosing patient conditions. Considering this, it is challenging to convince providers that AI-based solutions are cost-effective, efficient, and safe solutions that offer convenience to doctors as well as better care for patients.

Opportunity: Increasing focus on developing human-aware AI systems

The actual projections aimed during the emergence of AI technologies were to make them human-aware, i.e., developing models with the characteristics of human thinking. However, creating interactive and scalable machines remains a challenge for the developers of AI machines. Additionally, increasing human interference with AI techniques has introduced new research challenges, i.e., interpretation and presentation challenges such as interaction issues with automating parts and intelligent control of crowdsourcing parts. Interpretation challenges include challenges faced by AI machines in understanding human input, such as knowledge and specific directives. Presentation challenges include issues related to delivering the AI system’s output and feedback. Thus, the development of human-aware AI systems remains the foremost opportunity for AI developers.

Challenge: Concerns regarding data privacy

The main factor that is predicted to be a challenge for AI adoption among businesses is data privacy. AI technologies process data and generate outputs. Machine learning, deep learning, NLP, facial recognition, and emotion detection technologies feed on the stored data and provide actionable results. These technologies churn out useful data from enormous volumes of data and help businesses make critical decisions. Customers fear about their personal data being collected and used by AI; this data may include information such as their location and spending habits. To safeguard this information is a challenge for enterprises. Many nations follow privacy regulations to protect their citizens’ privacy and avoid any misuse. To maintain public trust and the ethical use of data by AI, many organizations, along with the governments of various nations, are working toward creating a robust AI-based framework.

Scope of the Report

Report Metric

Details

Market size available for years

2015–2025

Base year considered

2017

Forecast period

2018–2025

Forecast units

USD million and billion.

Segments covered

Offering, Technology, End-use Application, End-User and Region

Geographies covered

North America, Europe, APAC, Rest of the World (South America, the Middle East and Africa)

Companies covered

Intel (US), NVIDIA (US), Siemens Healthineers (Germany), Medtronic (Ireland), Micron Technology (US), IBM (US), Microsoft (US), Google Inc (US), Amazon Web Services (US), (General Electric (US), CloudMedx (US)

The research report categorizes artificial intelligence in healthcare market to forecast the revenues and analyze the trends in each of the following sub-segments:

Artificial intelligence in healthcare market, by Offering

  • Hardware
  • Software
  • Services

Artificial intelligence in healthcare market, by Technology

  • Machine Learning
  • Natural Language Processing
  • Context-Aware Computing
  • Computer Vision
  • Querying Method

Artificial intelligence in healthcare market, by End-use Application

  • Patient data and Risk analysis
  • Inpatient care & Hospital Management
  • Medical Imaging and Diagnostics
  • Lifestyle Management and Monitoring
  • Virtual Assistant
  • Drug Discovery
  • Research
  • Healthcare Assistance Robots
  • Precision Medicine
  • Emergency Room & Robot Assisted Surgery
  • Wearables
  • Mental Health
  • Fraud Detection
  • Cybersecurity
  • Clinical Trial Participant Identifier
  • Others

Artificial intelligence in healthcare market, by End User

  • Hospitals and Providers
  • Patients
  • Pharmaceutical and Biotechnology companies
  • Healthcare Payers
  • Others (ACOs and MCOs) 

Artificial intelligence in healthcare market, by Region

  • North America
  • Europe
  • Asia Pacific (APAC)
  • Rest of the world (ROW)

Key Market Players

Intel (US), NVIDIA (US), Siemens Healthcare (Germany), Medtronic (Ireland), Micron Technology (US), IBM (US), Microsoft (US), Google (US), Amazon Web Services (US), (General Electric (US), CloudMedx (US)

Recent Developments

In June 2018 Medtronic and its strategic technology partner, IBM (US) Watson Health, announced the commercial launch of Sugar.IQ smart diabetes assistant, a first-of-its-kind intelligent app designed to simplify and improve daily diabetes management. The Sugar.IQ smart diabetes assistant leverages AI and analytic technologies from IBM Watson Health to continually analyze how an individual's glucose level responds to food intake, insulin dosages, daily routines, and other factors, such as information provided by the app user.

In April 2018, Fast Track Diagnostics, a Siemens Healthineers company, launched a new molecular thermocycler, the Fast Track cycler1, and the complementary new FastFinder2 software at the 28th European Congress of Clinical Microbiology and Infectious Diseases (ECCMID 2018). The Fast Track cycler is a compact platform that enables laboratories of all sizes to implement molecular testing with simplicity and speed, while the FastFinder software improves workflows due to AI-powered automation.

In February 2018, GE Healthcare launched its new generation of high-end radiology ultrasound system, the LOGIQ E10. This fully digital system integrates AI technology, cloud connectivity, and advanced algorithms to acquire and reconstruct data faster than ever before. As a result, it enables confident diagnosis with comprehensive tools and concise workflow. The device is embedded with advanced GPU hardware technology that acquires and reconstructs data from MRI or CT system, enabling 48 times the data throughput and 10 times the processing power of previous systems.

In December 2017, IBM unveiled its next-generation Power Systems Servers incorporating its newly designed POWER9 processor. Built specifically for compute-intensive AI workloads, the new POWER9 systems are capable of improving the training times of deep learning frameworks by nearly 4 times, allowing enterprises to build more accurate AI applications faster.

Critical questions the report answers:

  • Where will all these developments take the Market industry in the long term?
  • What are the upcoming trends for the Artificial Intelligence in Healthcare Market?
  • Which segment provides the most opportunity for growth?
  • Who are the leading vendors operating in this market?
  • What are the opportunities for new market entrants?

To speak to our analyst for a discussion on the above findings, click Speak to Analyst

Table of Contents

1 Introduction (Page No. - 20)
    1.1 Study Objectives
    1.2 Market Definition
    1.3 Study Scope
           1.3.1 Markets Covered
           1.3.2 Years Considered
    1.4 Currency
    1.5 Stakeholders

2 Research Methodology (Page No. - 23)
    2.1 Research Data
           2.1.1 Secondary and Primary Research
                    2.1.1.1 Key Industry Insights
           2.1.2 Secondary Data
                    2.1.2.1 List of Major Secondary Sources
                    2.1.2.2 Secondary Sources
           2.1.3 Primary Data
                    2.1.3.1 Primary Interviews With Experts
                    2.1.3.2 Breakdown of Primaries
                    2.1.3.3 Primary Sources
    2.2 Market Size Estimation
           2.2.1 Bottom-Up Approach
                    2.2.1.1 Approach for Capturing the Market Share By Bottom-Up Analysis (Demand Side)
           2.2.2 Top-Down Approach
                    2.2.2.1 Approach for Capturing the Market Share By Top-Down Analysis (Supply Side)
    2.3 Market Breakdown and Data Triangulation
    2.4 Research Assumptions

3 Executive Summary (Page No. - 33)

4 Premium Insights (Page No. - 40)
    4.1 Attractive Opportunities in Artificial Intelligence in Healthcare Market
    4.2 Market, By Offering
    4.3 Market, By Technology
    4.4 Europe: Market, By End User and Country
    4.5 Market, By Country

5 Market Overview (Page No. - 44)
    5.1 Introduction
    5.2 Market Dynamics
           5.2.1 Drivers
                    5.2.1.1 Increasingly Large and Complex Data Set
                    5.2.1.2 Growing Demand to Reduce Healthcare Costs
                    5.2.1.3 Improving Computing Power and Declining Hardware Cost
                    5.2.1.4 Growing Number of Cross-Industry Partnerships and Collaborations
                    5.2.1.5 Rising Need for Improvised Healthcare Services Due to Imbalance Between Health Workforce and Patients
           5.2.2 Restraints
                    5.2.2.1 Reluctance Among Medical Practitioners to Adopt AI-Based Technologies
                    5.2.2.2 Lack of Skilled AI Workforce and Ambiguous Regulatory Guidelines for Medical Software
           5.2.3 Opportunities
                    5.2.3.1 Growing Potential of AI-Based Tools for Elderly Care
                    5.2.3.2 Increasing Focus on Developing Human-Aware AI Systems
           5.2.4 Challenges
                    5.2.4.1 Lack of Curated Healthcare Data
                    5.2.4.2 Concerns Regarding Data Privacy
                    5.2.4.3 Lack of Interoperability Between AI Solutions Offered By Different Vendors
    5.3 Value Chain Analysis
    5.4 Case Studies
           5.4.1 Mayo Clinic’s Centre for Individualized Medicine Collaborated With Tempus to Personalize Cancer Treatment
           5.4.2 Microsoft Collaborated With Cleveland Clinic to Identify Potential At-Risk Patients Under ICU Care
           5.4.3 NVIDIA and Massachusetts General Hospital Partnered to Use Artificial Intelligence for Advanced Radiology, Pathology, & Genomics
           5.4.4 Microsoft Partnered With Weil Cornell Medicine to Develop AI-Powered Chatbot
           5.4.5 Partners Healthcare and GE Healthcare Entered Into 10-Year Collaboration for Integrating AI Across Continuum of Care

6 Artificial Intelligence in Healthcare Market, By Offering (Page No. - 58)
    6.1 Introduction
    6.2 Hardware
           6.2.1 Processor
                    6.2.1.1 MPU
                    6.2.1.2 GPU
                    6.2.1.3 FPGA
                    6.2.1.4 ASIC
           6.2.2 Memory
                    6.2.2.1 High-Bandwidth Memory is Being Developed and Deployed for AI Applications, Independent of Its Computing Architecture
           6.2.3 Network
                    6.2.3.1 NVIDIA (US), Intel (US) and Mellanox Technologies (Israel) are the Key Providers of Network Interconnect Adapters for AI Applications
    6.3 Software
           6.3.1 AI Solutions
                    6.3.1.1 On-Premises
                               6.3.1.1.1 Data-Sensitive Enterprises Prefer On-Premises’ Advanced Nlp and Ml Tools to Be Used in AI Solutions
                    6.3.1.2 Cloud
                               6.3.1.2.1 The Cloud Provides Additional Flexibility for Business Operations and Real-Time Deployment Ease to Companies That are Implementing Real-Time Analytics
           6.3.2 AI Platform
                    6.3.2.1 Machine Learning Framework
                               6.3.2.1.1 Major Tech Companies Such as Google, IBM, Microsoft are Developing and Offering Their Own Ml Frameworks
                    6.3.2.2 Application Program Interface (Api)
                               6.3.2.2.1 Apis are Used When Programming Graphical User Interface (Gui) Components
    6.4 Services
           6.4.1 Deployment & Integration
                    6.4.1.1 Need for Deployment and Integration Services for AI Hardware and Software Solutions is Supplementing the Growth of Services
           6.4.2 Support & Maintenance
                    6.4.2.1 The Ultimate Objective of Maintenance Services is to Keep the System at an Acceptable Standard

7 Artificial Intelligence in Healthcare Market, By Technology (Page No. - 71)
    7.1 Introduction
    7.2 Machine Learning
           7.2.1 Deep Learning
                    7.2.1.1 Deep Learning Enables A Machine to Build A Hierarchical Representation.
           7.2.2 Supervised Learning
                    7.2.2.1 Classification and Regression are Major Segmentation of Supervised Learning
           7.2.3 Reinforcement Learning
                    7.2.3.1 Reinforcement Learning Allows Systems and Software to Determine Ideal Behaviour for Maximizing Performance of the Systems
           7.2.4 Unsupervised Learning
                    7.2.4.1 Unsupervised Learning Include Clustering Methods Consisting of Algorithms With Unlabelled Training Data
           7.2.5 Others
    7.3 Natural Language Processing
           7.3.1 Nlp is Widely Used By the Clinical and Research Community in Healthcare
    7.4 Context-Aware Computing
           7.4.1 Development of More Sophisticated Hard and Soft Sensors has Accelerated the Growth of Context-Aware Computing
    7.5 Computer Vision
           7.5.1 Computer Vision Technology has Shown Significant Applications in Surgery and Therapy
    7.6 Querying Method

8 Artificial Intelligence in Healthcare Market, By End-Use Application (Page No. - 79)
    8.1 Introduction
    8.2 Patient Data and Risk Analysis
           8.2.1 Growth in Healthcare Data has Escalated Patient Data and Risk Analysis Application
    8.3 Inpatient Care & Hospital Management
           8.3.1 Demand to Reduce the Operational Cost in Hospitals to Generate Demand for AI-Based In-Patient Care and Hospital Management
    8.4 Medical Imaging & Diagnostics
           8.4.1 Growth in Medical Imaging Data has Propelled the Growth of Medical Imaging and Diagnostics Application
    8.5 Lifestyle Management & Monitoring
           8.5.1 AI Solutions for Lifestyle Management and Monitoring Helps Patients in Making Healthier Lifestyle Changes
    8.6 Virtual Assistant
           8.6.1 Increasing Demand to Improve Follow-Up Care, Especially for Patients With Chronic Diseases, is Driving the Growth of Virtual Assistants
    8.7 Drug Discovery
           8.7.1 AI to Reduce the Time and Cost Required in Drug Discovery
    8.8 Research
           8.8.1 Growing Adoption of Different Types of AI Algorithms Among Bioinformatics Researchers, Especially for Classifying and Mining Their Databases, is the Key Application of AI in Research
    8.9 Healthcare Assistance Robots
           8.9.1 Healthcare Assistance Robots have Been Adopted in Several Areas That Directly Affect Patient Care
    8.10 Precision Medicine
           8.10.1 AI is Expected to Fulfill the Demand for Personalized Treatment Plans for Patients Administered With Precision Medicine
    8.11 Emergency Room & Robot-Assisted Surgery
           8.11.1 Limited Workforce in Emergency Rooms and Demand to Support Clinicians With Surgical Data to Drive the Growth of AI in Emergency Room and Surgery
    8.12 Wearables
           8.12.1 Wearable Devices are Clinically Useful for Improving Real-Time Monitoring of Patients
    8.13 Mental Health
           8.13.1 Increase in Mental Disorders Across the World is the Key Factor Supporting the Growth of Mental Health Application
    8.14 Fraud Detection 
    8.15 Cybersecurity 
    8.16 Clinical Trial Participant Identifier
    8.17 Others

9 Artificial Intelligence in Healthcare Market, By End User (Page No. - 99)
    9.1 Introduction
    9.2 Hospitals and Providers
           9.2.1 AI Can Be Utilized to Predict and Prevent Readmissions, and Improve Operations Among Hospitals and Providers
    9.3 Patients
           9.3.1 Smartphone Applications and Wearables to Drive the Adoption of AI Among Patients
    9.4 Pharmaceutical and Biotechnology Companies
           9.4.1 Applications Such as Drug Discovery, Precision Medicine, and Research to Drive AI in Pharmaceutical and Biotechnology Companies
    9.5 Healthcare Payers
           9.5.1 Healthcare Payers Use AI Tools Mainly for Managing Risk, Identifying Claims Trends, and Maximizing Payment Accuracy
    9.6 Others
           9.6.1 Patient Data and Risk Analytics and Healthcare Assistance Robots to Drive the Growth of AI in Acos and Mcos

10 Artificial Intelligence in Healthcare Market, By Region (Page No. - 111)
     10.1 Introduction
     10.2 North America
             10.2.1 US
                        10.2.1.1 High Healthcare Spending to Complement the Growth of AI in the US
             10.2.2 Canada
                        10.2.2.1 Continuous Research on Nlp and Ml Across Research Institutions and Universities in Canada Propels the Artificial Intelligence in Healthcare Market
             10.2.3 Mexico
                        10.2.3.1 AI-Enabled Devices for the Healthcare Sector have Been Gaining Traction in Mexico
     10.3 Europe
             10.3.1 Germany
                        10.3.1.1 Rising Healthcare Data Generation in the Country Will Be A Key Driving Factor for the Growth of the Market
             10.3.2 UK
                        10.3.2.1 Large Volume of Data Generated By Nhs and Digital Health Solutions have Paved the Way for AI in the UK
             10.3.3 France
                        10.3.3.1 Healthcare It in France has Witnessed Considerable Implementation of AI Over the Last Decade
             10.3.4 Italy
                        10.3.4.1 Development of Electronic Health Records and Aging Population to Drive the Market in Italy
             10.3.5 Spain
                        10.3.5.1 Growing Awareness of AI in Spain to Drive the AI in Healthcare Market
             10.3.6 Rest of Europe
     10.4 Asia Pacific
             10.4.1 China
                        10.4.1.1 High Spending By the Government in Healthcare and Official Plans to Digitize Medical Records to Drive the Market in China
             10.4.2 Japan
                        10.4.2.1 Aging Population to Drive the Growth of AI in Japan
             10.4.3 South Korea
                        10.4.3.1 Quality Healthcare Services and Rapid Expansion of Medical Insurance Coverage are Among the Driving Factors of Market in South Korea
             10.4.4 India
                        10.4.4.1 Developing It Infrastructure in the Country and AI-Friendly Initiatives By the Government are the Key Factors Supporting the Growth of AI in India
             10.4.5 Rest of Asia Pacific
     10.5 Rest of the World
             10.5.1 South America
                        10.5.1.1 Increasing Awareness About Potential Applications of AI in Healthcare is Driving the Growth of the Market in South America
             10.5.2 Middle East and Africa
                        10.5.2.1 Growing Healthcare Expenditure in the Middle East and North Africa is A Key Growth Driver of Artificial Intelligence in Healthcare Market

11 Competitive Landscape (Page No. - 138)
     11.1 Overview
     11.2 Ranking of Players, 2017
     11.3 Competitive Scenario
             11.3.1 Product Developments and Launches
             11.3.2 Collaborations, Partnerships, and Strategic Alliances
             11.3.3 Acquisitions & Joint Ventures

12 Company Profiles (Page No. - 147)
     12.1 Key Players
(Business Overview, Products Offered, Recent Developments, SWOT Analysis, and MnM View)*
             12.1.1 NVIDIA
                        12.1.1.1 Business Overview
                        12.1.1.2 Products Offered
                        12.1.1.3 Recent Developments
                        12.1.1.4 SWOT Analysis
                        12.1.1.5 MnM View
             12.1.2 Intel
                        12.1.2.1 Business Overview
                        12.1.2.2 Products Offered
                        12.1.2.3 Recent Developments
                        12.1.2.4 SWOT Analysis
                        12.1.2.5 MnM View
             12.1.3 IBM
                        12.1.3.1 Business Overview
                        12.1.3.2 Products Offered
                        12.1.3.3 Recent Developments
                        12.1.3.4 SWOT Analysis
                        12.1.3.5 MnM View
             12.1.4 Google
                        12.1.4.1 Business Overview
                        12.1.4.2 Products Offered
                        12.1.4.3 Recent Developments
                        12.1.4.4 SWOT Analysis
                        12.1.4.5 MnM View
             12.1.5 Microsoft
                        12.1.5.1 Business Overview
                        12.1.5.2 Products Offered
                        12.1.5.3 Recent Developments
                        12.1.5.4 SWOT Analysis
                        12.1.5.5 MnM View
             12.1.6 General Electric (GE) Company
                        12.1.6.1 Business Overview
                        12.1.6.2 Products Offered
                        12.1.6.3 Recent Developments
                        12.1.6.4 MnM View
             12.1.7 Siemens Healthineers (A Strategic Unit of the Siemens Group)
                        12.1.7.1 Business Overview
                        12.1.7.2 Products Offered
                        12.1.7.3 Recent Developments
                        12.1.7.4 MnM View
             12.1.8 Medtronic
                        12.1.8.1 Business Overview
                        12.1.8.2 Products Offered
                        12.1.8.3 Recent Developments
                        12.1.8.4 MnM View
             12.1.9 Micron Technology
                        12.1.9.1 Business Overview
                        12.1.9.2 Products Offered
                        12.1.9.3 Recent Developments
                        12.1.9.4 MnM View
             12.1.10 Amazon Web Services (AWS)
                        12.1.10.1 Business Overview
                        12.1.10.2 Products Offered
                        12.1.10.3 Recent Developments
                        12.1.10.4 MnM View
* Business Overview, Products Offered, Recent Developments, SWOT Analysis, and MnM View Might Not Be Captured in Case of Unlisted Companies.
     12.2 Other Major Companies
             12.2.1 Johnson & Johnson Services
             12.2.2 Koninklijke Philips
             12.2.3 General Vision
     12.3 Company Profiles, By Application
             12.3.1 Patient Data & Risk Analysis
                        12.3.1.1 Cloudmedx
                        12.3.1.2 Oncora Medical
                        12.3.1.3 Zephyr Health
                        12.3.1.4 Sentrian
                        12.3.1.5 Careskore
                        12.3.1.6 Linguamatics
             12.3.2 Medical Imaging & Diagnostics
                        12.3.2.1 Enlitic
                        12.3.2.2 Bay Labs
                        12.3.2.3 Butterfly Networks
                        12.3.2.4 Imagia Cybernetics
             12.3.3 Precision Medicine
                        12.3.3.1 Precision Health AI
                        12.3.3.2 Cota
                        12.3.3.3 Fdna
             12.3.4 Drug Discovery
                        12.3.4.1 Recursion Pharmaceuticals
                        12.3.4.2 Atomwise
                        12.3.4.3 Deep Genomics
                        12.3.4.4 Cloud Pharmaceuticals
             12.3.5 Lifestyle Management & Monitoring
                        12.3.5.1 Welltok
                        12.3.5.2 Vitagene
                        12.3.5.3 Lucina Health
             12.3.6 Virtual Assistants
                        12.3.6.1 Next It (A Verint Systems Company)
                        12.3.6.2 Babylon
                        12.3.6.3 Mdlive
             12.3.7 Wearables
                        12.3.7.1 Magnea
                        12.3.7.2 Physiq
                        12.3.7.3 Cyrcadia Health
             12.3.8 Emergency Room & Surgery
                        12.3.8.1 Caresyntax
                        12.3.8.2 Gauss Surgical
                        12.3.8.3 Perceive3D
                        12.3.8.4 Maxq AI
             12.3.9 In-Patient Care & Hospital Management
                        12.3.9.1 Qventus
                        12.3.9.2 Workfusion
             12.3.10 Research
                        12.3.10.1 Icarbonx
                        12.3.10.2 Desktop Genetics
             12.3.11 Mental Health
                        12.3.11.1 Ginger.Io
                        12.3.11.2 X2ai
                        12.3.11.3 Biobeats
             12.3.12 Healthcare Assistance Robots
                        12.3.12.1 Pillo
                        12.3.12.2 Catalia Health

13 Appendix (Page No. - 207)
     13.1 Insights From Industry Experts
     13.2 Discussion Guide
     13.3 Knowledge Store: Marketsandmarkets’ Subscription Portal
     13.4 Available Customizations
     13.5 Related Reports
     13.6 Author Details


List of Tables (103 Tables)

Table 1 Increase in Neuroimaging and Genetics Data, and Complexity Relative to Computational Power
Table 2 Price Comparison: AI Chipsets (Leading Companies)
Table 3 Artificial Intelligence in Healthcare Market, By Offering, 2015–2025 (USD Million)
Table 4 Market, By Hardware, 2015–2025 (USD Million)
Table 5 Market for Hardware, By Region, 2015–2025 (USD Million)
Table 6 Market, By Processor, 2015–2025 (USD Million)
Table 7 Market for Offering, By Software, 2015–2025 (USD Million)
Table 8 Market for Software, By Region, 2015–2025 (USD Million)
Table 9 Market for Solution, By Deployment, 2015–2025 (USD Million)
Table 10 Market for Software, By Platform, 2015–2025 (USD Million)
Table 11 Market, By Services, 2015–2025 (USD Million)
Table 12 Market for Services, By Region, 2015–2025 (USD Million)
Table 13 Market, By Technology, 2015–2025 (USD Million)
Table 14 Market for Machine Learning, By Type, 2015–2025 (USD Million)
Table 15 AI in Healthcare Market for Natural Language Processing, By Type, 2015–2025 (USD Million)
Table 16 Market for Context-Aware Computing, By Type, 2015–2025 (USD Million)
Table 17 Market, By End-Use Application, 2015–2025 (USD Million)
Table 18 Market for Patient Data and Risk Analysis, By Region, 2015–2025 (USD Million)
Table 19 Market for Patient Data and Risk Analysis, By End User, 2015–2025 (USD Million)
Table 20 Market for In-Patient Care & Hospital Management, By Region, 2015–2025 (USD Million)
Table 21 Market for In-Patient Care and Hospital Management, By End User, 2015–2025 (USD Million)
Table 22 Market for Medical Imaging and Diagnostics, By Region, 2015–2025 (USD Million)
Table 23 Market for Medical Imaging and Diagnostics, By End User, 2015–2025 (USD Million)
Table 24 Market for Lifestyle Management & Monitoring, By Region, 2015–2025 (USD Million)
Table 25 Market for Lifestyle Management & Monitoring, By End User, 2015–2025 (USD Million)
Table 26 Market for Virtual Assistant, By Region, 2015–2025 (USD Million)
Table 27 Market for Virtual Assistant, By End User, 2015–2025 (USD Million)
Table 28 Market for Drug Discovery, By Region, 2015–2025 (USD Million)
Table 29 AI in Healthcare Market for Drug Discovery, By End User, 2015–2025 (USD Million)
Table 30 Market for Research, By Region, 2015–2025 (USD Million)
Table 31 Market for Research, By End User, 2015–2025 (USD Million)
Table 32 Market for Healthcare Assistance Robots, By Region, 2015–2025 (USD Million)
Table 33 Artificial Intelligence in Healthcare Market for Healthcare Assistance Robots, By End User, 2015–2025 (USD Million)
Table 34 Market for Precision Medicine, By Region, 2015–2025 (USD Million)
Table 35 Market for Precision Medicine, By End User, 2015–2025 (USD Million)
Table 36 Market for Emergency Room & Robot Assisted Surgery, By Region, 2015–2025 (USD Million)
Table 37 Market for Emergency Room & Robot Assisted Surgery, By End User, 2015–2025 (USD Million)
Table 38 Market for Wearables, By Region, 2015–2025 (USD Million)
Table 39 Market for Wearables, By End User, 2015–2025 (USD Million)
Table 40 Market for Mental Health, By Region, 2015–2025 (USD Million)
Table 41 Market for Mental Health, By End User, 2015–2025 (USD Million)
Table 42 Market for Fraud Detection, By Region, 2015–2025 (USD Million)
Table 43 Market for Fraud Detection, By End User, 2015–2025 (USD Million)
Table 44 Market for Cybersecurity, By Region, 2015–2025 (USD Million)
Table 45 Market for Cybersecurity, By End User, 2015–2025 (USD Million)
Table 46 AI in Healthcare Market for Clinical Trial Participant Identifier, By Region, 2015–2025 (USD Million)
Table 47 Market for Clinical Trial Participant Identifier, By End User, 2015–2025 (USD Million)
Table 48 Market, By End User, 2015–2025 (USD Million)
Table 49 Market for Hospitals and Providers, By Application, 2015–2025 (USD Million)
Table 50 Market for Hospitals and Providers, By Region, 2015–2025 (USD Million)
Table 51 Market for Patients, By Application, 2015–2025 (USD Million)
Table 52 Market for Patients, By Region, 2015–2025 (USD Million)
Table 53 Market for Pharmaceutical and Biotechnology Companies, By Application, 2015–2025 (USD Million)
Table 54 Market for Pharmaceutical and Biotechnology Companies, By Region, 2015–2025 (USD Million)
Table 55 Market for Healthcare Payers, By Application, 2015–2025 (USD Million)
Table 56 Market for Healthcare Payers, By Region, 2015–2025 (USD Million)
Table 57 Market for Others, By Application, 2015–2025 (USD Million)
Table 58 Artificial Intelligence in Healthcare Market for Others, By Region, 2015–2025 (USD Million)
Table 59 Market, By Region, 2015–2025 (USD Million)
Table 60 Market in North America, By Country, 2015–2025(USD Million)
Table 61 Market in North America, By End User, 2015–2025 (USD Million)
Table 62 Market in North America, By Offering, 2015–2025 (USD Million)
Table 63 Market in the US, By End User, 2015–2025 (USD Million)
Table 64 AI in Healthcare Market in the US, By Offering, 2015–2025 (USD Million)
Table 65 Market in Canada, By End User, 2015–2025 (USD Million)
Table 66 Market in Canada, By Offering, 2015–2025 (USD Million)
Table 67 Market in Mexico, By End User, 2015–2025 (USD Million)
Table 68 Market in Mexico, By Offering, 2015–2025 (USD Million)
Table 69 Market in Europe, By Country, 2015–2025(USD Million)
Table 70 Market in Europe, By End User, 2015–2025 (USD Million)
Table 71 Market in Europe, By Offering, 2015–2025 (USD Million)
Table 72 Market in Germany, By End User, 2015–2025 (USD Million)
Table 73 Market in Germany, By Offering, 2015–2025 (USD Million)
Table 74 Market in the UK, By End User, 2015–2025 (USD Million)
Table 75 Market in the UK, By Offering, 2015–2025 (USD Million)
Table 76 Market in France, By End User, 2015–2025 (USD Million)
Table 77 Market in France, By Offering, 2015–2025 (USD Million)
Table 78 Market in Italy, By End User, 2015–2025 (USD Million)
Table 79 Artificial Intelligence in Healthcare Market in Italy, By Offering, 2015–2025 (USD Million)
Table 80 Market in Spain, By End User, 2015–2025 (USD Million)
Table 81 Market in Spain, By Offering, 2015–2025 (USD Million)
Table 82 Market in Rest of Europe, By End User, 2015–2025 (USD Million)
Table 83 Market in Rest of Europe, By Offering, 2015–2025 (USD Million)
Table 84 AI in Healthcare Market in APAC, By Country, 2015–2025 (USD Million)
Table 85 Market in APAC, By End User, 2015–2025 (USD Million)
Table 86 Market in APAC, By Offering, 2015–2025 (USD Million)
Table 87 Market in China, By End User, 2015–2025 (USD Million)
Table 88 Market in China, By Offering, 2015–2025 (USD Million)
Table 89 Market in Japan, By End User, 2015–2025 (USD Million)
Table 90 Market in Japan, By Offering, 2015–2025 (USD Million)
Table 91 Market in South Korea, By End User, 2015–2025 (USD Million)
Table 92 Market in South Korea, By Offering, 2015–2025 (USD Million)
Table 93 Market in India, By End User, 2015–2025 (USD Million)
Table 94 Market in India, By Offering, 2015–2025 (USD Million)
Table 95 Market in Rest of APAC, By End User, 2015–2025 (USD Million)
Table 96 Market in Rest of APAC, By Offering, 2015–2025 (USD Million)
Table 97 Market in RoW, By Region, 2015–2025 (USD Million)
Table 98 Market in RoW, By End User, 2015–2025 (USD Million)
Table 99 Market in RoW, By Offering, 2015–2025 (USD Million)
Table 100 Market in South America, By End User, 2015–2025 (USD Million)
Table 101 Market in South America, By Offering, 2015–2025 (USD Million)
Table 102 Market in Middle East & Africa, By End User, 2015–2025 (USD Million)
Table 103 Artificial Intelligence in Healthcare Market in Middle East & Africa, By Offering, 2015–2025 (USD Million)


List of Figures (49 Figures)

Figure 1 Artificial Intelligence in Healthcare Market: Research Design
Figure 2 Market Size Estimation Methodology: Bottom-Up Approach
Figure 3 Market Size Estimation Methodology: Top-Down Approach
Figure 4 Data Triangulation
Figure 5 Assumptions for the Research Study
Figure 6 AI in Healthcare Market, By Offering, 2018 vs 2025 (USD Million)
Figure 7 Market, By Processor, 2018 vs 2025 (USD Million)
Figure 8 Market, By Technology, 2015-2025 (USD Million)
Figure 9 Artificial Intelligence in Healthcare Market, By Application, 2018 vs 2025 (USD Million)
Figure 10 Market, By End User, 2018 vs 2025 (USD Million)
Figure 11 Market, By Region, 2018
Figure 12 Growing Big Data in Healthcare and Increasing Adoption of AI-Based Tools in Healthcare Facilities are Major Factors Driving Market Growth
Figure 13 Software to Hold Largest Share of Market During Forecast Period
Figure 14 Market for Machine Learning to Hold Largest Size From 2018 to 2025
Figure 15 Germany Expected to Hold Largest Share of Market in 2018 in Europe
Figure 16 US to Hold Largest Share of Market in 2018
Figure 17 Increasingly Large and Complex Data Set and Growing Demand to Reduce Healthcare Costs are Driving Market Growth
Figure 18 Types of Healthcare Breaches Reported to U.S. Department of Health and Human Services
Figure 19 Artificial Intelligence in Healthcare Market Value Chain in 2017
Figure 20 Software to Hold Largest Size of Market During Forecast Period
Figure 21 AI in Healthcare Processor Market for GPU to Grow at Highest CAGR During Forecast Period
Figure 22 North America to Hold Largest Market in Market for Software During Forecast Period
Figure 23 Machine Learning to Hold Largest Share of Market During Forecast Period
Figure 24 Artificial Intelligence in Healthcare Market for Medical Imaging & Diagnostics to Grow at Highest CAGR During Forecast Period
Figure 25 North America to Lead Lifestyle Management & Monitoring Application During Forecast Period
Figure 26 North America to Hold Largest Market in Research Application During Forecast Period
Figure 27 North America to Hold Largest Share in Emergency Room & Surgery Application in 2018
Figure 28 Hospitals and Providers to Hold Largest Share of Market in 2018 & 2025
Figure 29 Precision Medicine Application to Witness Highest CAGR in Market for Pharmaceutical & Biotechnology Companies During Forecast Period
Figure 30 China & US are Emerging as New Hot Spots in Market
Figure 31 North America to Dominate Market During Forecast Period
Figure 32 North America: Snapshot of Market
Figure 33 Europe: Snapshot of Artificial Intelligence in Healthcare Market
Figure 34 Hospitals & Providers Held Largest Share in European Market in 2018
Figure 35 APAC: Snapshot of Market
Figure 36 Services to Witness Highest CAGR in Market During Forecast Period
Figure 37 RoW: Snapshot of Market
Figure 38 Key Developments Adopted By Top Players in Artificial Intelligence in Healthcare Market From 2015 to Mid-2018
Figure 39 Ranking of Key Companies in Market (2017)
Figure 40 NVIDIA: Company Snapshot
Figure 41 Intel: Company Snapshot
Figure 42 IBM: Company Snapshot
Figure 43 Google: Company Snapshot
Figure 44 Microsoft: Company Snapshot
Figure 45 GE: Company Snapshot
Figure 46 Siemens Healthineers: Company Snapshot
Figure 47 Medtronic: Company Snapshot
Figure 48 Micron Technology: Company Snapshot
Figure 49 AWS: Company Snapshot

The study involved 4 major activities in estimating the current size of the artificial intelligence in healthcare market. Exhaustive secondary research has been conducted to collect information about the market, the peer market, and the parent market. Validating findings, assumptions, and sizing with industry experts across the value chain through primary research has been the next step. Both, top-down and bottom-up approaches have been employed to estimate the complete market size. In the subsequent steps, market breakdown and data triangulation methods have been used to estimate the market size of segments and subsegments.

Secondary Research

The research methodology used to estimate and forecast the AI in healthcare market begins with capturing data on revenues of the key vendors in the market through secondary research. This study involves the use of extensive secondary sources, directories, and databases such as Hoovers, Bloomberg Businessweek, Factiva, and OneSource to identify and collect information useful for the technical and commercial study of the artificial intelligence in healthcare market. Moreover, secondary sources include annual reports, press releases, and investor presentations of companies; white papers, certified publications, and articles from recognized authors; directories; and databases. Secondary research has been mainly done to obtain key information about the industry’s supply chain, the market’s value chain, the total pool of key players, market classification and segmentation according to industry trends, geographic markets, and key developments from both market- and technology-oriented perspectives.

Primary Research

In the primary research process, various primary sources from both supply and demand sides were interviewed to obtain the qualitative and quantitative information relevant to artificial intelligence in healthcare market. Primary sources from the supply side include experts such as CEOs, vice presidents, marketing directors, technology and innovation directors, application developers, application users, and related executives from various key companies and organizations operating in the ecosystem of the AI in healthcare market.


Artificial Intelligence in Healthcare Market

To know about the assumptions considered for the study, download the pdf brochure

Market Size Estimation

Both, top-down and bottom-up approaches have been used to estimate and validate the overall size of the artificial intelligence in healthcare market. These methods have also been used extensively to estimate the size of various market subsegments. The research methodology used to estimate the market size includes the following:

  • Key players in major applications and markets have been identified through extensive secondary research.
  • The industry’s supply chain and market size, in terms of value, have been determined through primary and secondary research processes.
  • All percentage shares, splits, and breakdowns have been determined using secondary sources and verified through primary sources.

Data Triangulation

After arriving at the overall market size using the 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 breakdown procedures have been employed, wherever applicable. The data have been triangulated by studying various factors and trends from both demand and supply sides.

Report Objectives

  • To describe and forecast the artificial intelligence (AI) in healthcare market, in terms of value, by offering, technology, end-use application, and end user
  • To describe and forecast the AI in healthcare market, in terms of value, by region—North America, Europe, Asia Pacific (APAC), and Rest of the World (RoW)
  • To provide detailed information regarding major factors influencing the market growth (drivers, restraints, opportunities, and challenges)
  • To strategically analyze micromarkets with respect to individual growth trends, prospects, and contributions to the total market
  • To profile key players and comprehensively analyze their market position in terms of ranking and core competencies, along with detailing competitive landscape for market leaders
  • To analyze the competitive developments such as joint ventures, collaborations, agreements, contracts, partnerships, mergers & acquisitions, new product developments, and research and development (R&D) in the artificial intelligence in healthcare market

Scope of the Report:


Report Metric

Details

Market size available for years

2015–2025

Base year

2017

Forecast period

2018–2025

Units

Value, USD

Segments covered

Offering, Technology, End-Use Application, End User

Geographic regions covered

North America, APAC, Europe, and RoW

Companies covered

NVIDIA (US), Intel (US), IBM (US), Google (US), Microsoft (US), AWS (US), General Vision (US), GE Healthcare (US), Siemens Healthineers (Germany), Medtronic plc (US), Johnson & Johnson (US), and Koninklijke Philips N.V. (Netherlands), among others

This report categorizes the artificial intelligence in healthcare market based on offering, technology, end-use application, end user, and region.

Market, by Offering:

  • Hardware
  • Software
  • Services

Market, by Technology:

  • Machine Learning
  • Natural Language Processing
  • Context-Aware Computing
  • Computer Vision

Market, by End-Use Application:

  • Patient Data & Risk Analysis
  • Medical Imaging & Diagnostics
  • Precision Medicine
  • Drug Discovery
  • Lifestyle Management & Monitoring
  • Virtual Assistant
  • Wearables
  • In-Patient Care & Hospital Management
  • Research
  • Emergency Room & Surgery
  • Mental Health
  • Healthcare Assistance Robots

Market, by End User:

  • Hospitals & Providers
  • Patients
  • Pharmaceutical & Biotechnology Companies
  • Healthcare Payers
  • Others (ACOs and MCOs)

Market, by Region:

  • North America
    • US
    • Canada
    • Mexico
  • Europe
    • Germany
    • France
    • UK
    • Italy
    • Spain
    • Rest of Europe
  • APAC
    • China
    • Japan
    • South Korea
    • India
    • Rest of APAC
  • RoW
    • Middle East & Africa
    • South America

Available Customizations

With the given market data, MarketsandMarkets offers customizations according to the company’s specific needs. The following customization options are available for the report:

Product Analysis

  • Product matrix that gives a detailed comparison of the product portfolio of each company
  • Country-wise breakdown of various end-user, including North America, Europe, APAC, and RoW
  • Unit shipment of hardware components, i.e., MPU, GPU, FPGA, and ASIC
  • Comprehensive coverage of funding/M&A activities, regulations followed in each region (North America, APAC, Europe, and RoW)

Company Information

  • Detailed analysis and profiling of additional market players (up to 5)
Report Code
SE 5225
Published ON
Dec, 2018
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