Natural Language Processing (NLP) in Healthcare and Life Sciences Market by Component (Technology and Services), Type (Rule-based, Statistical and Hybrid), Application, Deployment Mode (Cloud and On Premise) and Region - Global Forecast to 2021
[136 Pages Report] The NLP in Healthcare and life sciences market is estimated to grow from USD 1030.2 million in 2016 to USD 2650.2 million by 2021, at a Compound Annual Growth Rate (CAGR) of 20.8% during the forecast period. The base year considered for the study is 2015 and the forecast period is from 2016 to 2021. Digital transformation of medicine, increasing volume of clinical data, and growing adoption of Electronic Medical Records (EMRs) is expected to be driving the growth of the market in the coming years.
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NLP is a branch of Artificial Intelligence (AI) primarily concerned with reducing the human-machine gap. As NLP is becoming crucial with day to day communication, solution providers are focusing on designing the software that can understand, analyze, and generate languages that can be understood by humans. Moreover, there is a growing demand for automated voice recognition systems that automatically respond to customers queries. Natural Language Processing (NLP) systems are getting deployed in the areas of business help centers and customer help services. Besides, there are several other applications of NLP for enhancing the overall customer experience.
Market Dynamics
Drivers
- Huge surge in clinical data
- Increase in the use of connected devices
- Evolving consumer needs
Restraints
- Limited access to clinical data
- Lack of institutional commitment
Opportunities
- Government policies and initiatives
- Integration of social media for assessing population health
Challenges
- Unstructured clinical notes and texts
Increase in the use of connected devices
The use of connected devices is increasing in the healthcare industry. Large volume of patient data is generated from wearables, mobile devices, and medical devices. With more than 40 pharma companies are using pharma sponsored applications, the use of mobile devices is growing in the healthcare sector. The applications that are supported with NLP technology are used by the most of pharma institutes worldwide. Therefore, the growth in use of connected devices is expected to be driving the growth of the market in the healthcare and life sciences market.
Objectives of the Study
This report aims to estimate the market size and future growth potential of the NLP in Healthcare and Life Sciences market across different segments such as component, type, application, deployment mode, and regions. The report also focuses on information regarding the key factors (drivers, restraints, opportunities, and challenges) influencing market growth. Additionally, the opportunities in the market are providing strategic profiles of the key players to stakeholders present in the market. Allowing the stakeholders to comprehensively analyze the core competencies, and to draw the competitive landscape of the market.
The research methodology used to estimate and forecast the NLP in healthcare and life sciences market begins with capturing data on key vendor revenues through secondary research Hoovers, Bloomberg BusinessWeek, Factiva, and OneSource, to identify and collect information useful for this technical, market-oriented, and commercial study of the global market. The vendor offerings are also taken into consideration to determine market segmentation. The bottom-up procedure was employed to arrive at the overall market size of the global NLP in healthcare and life sciences market from the revenue of the key players in the market. After arriving at the overall market size, the total market was split into several segments and sub-segments, which were then verified through primary research by conducting extensive interviews with key industry personnel, such as CEOs, VPs, directors, and executives. The data triangulation and market breakdown procedures were employed to complete the overall market engineering process and arrive at the exact statistics for all segments and sub segments. The breakdown of profiles of primary discussion participants is depicted in the below figure:
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The NLP in healthcare and life sciences market ecosystem comprises of players such as 3M (Minnesota, US), Cerner Corporation (Missouri, US.), IBM Corporation (New York, US), Microsoft Corporation (Washington, US), Nuance Communications inc (Massachusetts, US), Heath Fidelity(California, US), Linguamatics (Cambridge, UK), Dolbey Systems (Ohio, US), Apixio (San Mateo, US) and MModal IP PLC(Tennessee, U.S.).
Major Market Developments
- In September 2016, 3M acquired a medical coding solution provider company, Semfinder. This acquisition is aimed at boosting and enriching 3M’s healthcare records coding solutions
- In June 2016, IBM Watson Heath partnered with American Diabetes Association to help diabetes patients by collaborating IBM Watson’s computing technology with the association’s research information.
- In February 2016, Nuance Communications launched a cloud-based platform, Dragon Medical One to help physicians in clinical documentation
Key Target Audience for NLP in Healthcare and Life Sciences Market
- Medical Institutions/Organizations
- Medical Research Institutes
- NLP solution providers
- Hospitals
- Government councils
- Health information exchanges
- Health Information Service Providers (HISPs)
- Pharmaceutical companies
Scope of the Report
The research report categorizes the NLP in healthcare and life sciences market to forecast the revenues and analyze the trends in each of the following sub-segments:
By Component
- Technology
- Interactive Voice Response
- Optical Character Recognition
- Pattern and Image Recognition
- Auto Coding
- Classification and Categorization
- Text Analytics
- Speech Analytics
- Service
- Professional Services
- Support and Maintenance Services
NLP in Healthcare and Life Sciences Market By Application Area;
- Predictive Risk Analytics
- Automated Information Extraction
- Report Generation
- Machine Translation
- Others*
By Deployment Model
- Private
- Public
By Type
- Rule-Based NLP
- Statistical NLP
- Hybrid NLP
By Region
- North America
- Europe
- Asia-Pacific (APAC)
- Middle East and Africa (MEA)
- Latin America
Critical questions which the report answers
- Which region hold the maximum opportunity of growth in NLP in healthcare and life sciences market?
- The key developments undertaken by the vendors in the market.
Available Customizations
With the given market data, MarketsandMarkets offers customization as per the company’s specific requirements. The following customization options are available for the report:
Product Analysis
- Product matrix provides a detailed information and product comparison
Geographic Analysis
- Further breakdown of the North America NLP in healthcare and life sciences market
- Further breakdown of the Europe market
- Further breakdown of the APAC market
Company Information
- Detailed analysis and profiling of additional market players
The NLP in healthcare and life sciences market size is expected to grow from USD 1,030.2 million in 2016 to USD 2,650.2 million by 2021, at a Compound Annual Growth Rate (CAGR) of 20.8% during the forecast period. In the report, 2015 is considered the base year while the forecast period is 2016–2021. The major growth driver for the Natural Language Processing (NLP) in healthcare and life sciences market includes huge surge in clinical data, increase in the use of connected devices, and evolving consumer needs.
NLP is branch of artificial intelligence primarily concerned with reducing human machine gap. In healthcare sector NLP is expected to be playing a crucial role. With the digital transformation of medicine, huge surge in clinical data and growing adoption of Electronic Medical Records (EMR) is expected to be driving the adoption of NLP in the healthcare industry. EMRs contain only 20% of structured information while the rest of the information is available as free text. Thus, with the help of NLP techniques, accuracy can be enhanced by capturing and classifying the rich information contained in free-text clinical narratives.
The NLP in healthcare and life sciences market is segmented by component (technology and service), type, application, deployment mode, and region. Among components, technology segment is expected to grow with the highest CAGR, due to the demand for NLP technologies such as recognition, operational, and analytics technologies to enhance various processes.
In the services segment, professional services segment is the fastest growing segment as the professional service providers are focusing on delivering deep insights to assist in industrial interoperability, manage clinical data, and provide enhanced service experience to the patients.
Organizations in healthcare domain the are rapidly moving toward cloud based deployment of NLP technologies. The demand for cloud-based NLP technologies is increasing due to the numerous advantage offered by it, that include scalability, cost effectiveness, ease of use and simplified access.
Among region, North America is expected to be contributing largest in terms of revenue, for NLP technology vendors during the forecast period. This is because majority of initiatives done for NLP technologies have their origin in the region. The APAC region is expected to grow at the fastest rate, as majority of healthcare organizations are seeking the benefits of NLP technologies, that will help them provide personalized customer experience and process efficiency.
The rapid surge in amount of healthcare data is expected to be creating demand for the NLP technology as it is becoming crucial in identifying new insights to enhance patient outcomes.
Rule Based NLP
Rule Based NLP is one of the methods used for extracting coded segments by applied human developed rules. It is a knowledge based approach which analyses the linguistic phenomena. The technique performs lexical analysis which evaluates language and the set of data based on human rules. Rule based NLP is useful during the automation of the business processes. The rule based NLP is beneficial for satisfying the changing requirements of the healthcare industry. Moreover, with the introduction of ICD-10 coding, healthcare organizations must implement rules according to this code, which can be deployed with the help of rule based NLP.
Statistical Based NLP
The statistical based NLP approach provides better output when large volume of data is involved. Also, with the huge volume availability of text to speech corpora, this technique has shown remarkable success in last few years. The technique works by taking generated data according to unknown probability distribution and creating inferences, it thereby uses statistical probability distribution algorithm as well as inferences to produce desired results. Statistical based NLP is playing a crucial role in healthcare sector, as it is assisting the medical professionals and researchers in analyzing trends and patterns from the unstructured clinical data.
Hybrid NLP
This approach combines statistical based NLP and rule based NLP. To provide better results, this technique uses both the methods. This approach is becoming useful in various applications that include eCRM, sentiment analysis, report generation, as well as machine translation. Wide range of NLP systems are using both the approaches such as statistical as well as rule based model.
Critical questions the report answers:
- How is adoption rate of NLP technology across various region in healthcare sector?
- What are the key developments undertaken by the various players in the market?
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Limited access to clinical data and lack of institutional commitment is restraining the growth of the NLP in healthcare and life sciences market. The limited access to clinical data is restraining the growth of the market, because of confidentiality issues of patient data. Generally, researchers that are associated with a medical center can use the clinical notes with the consent of Institutional Review Board approval. However, these details cannot be shared with external NLP community.
Major vendors that offer NLP technology and services to healthcare and life science industry are 3M (Minnesota, US), Cerner Corporation (Missouri, US.), IBM Corporation(New York, US), Microsoft Corporation (Washington, US), Nuance Communications inc (Massachusetts, US), Heath Fidelity(California, US), Linguamatics(Cambridge, UK), Dolbey Systems (Ohio, US), Apixio (San Mateo, US) and MModal IP PLC(Tennessee, U.S.). These vendors have adopted different types of organic and inorganic growth strategies such as new product launches, partnerships & collaborations, and mergers & acquisitions to expand their offerings in the Natural Language Processing (NLP) in healthcare and life sciences market.
Table of Contents
1 Introduction (Page No. - 14)
1.1 Objective of the Study
1.2 Market Definition
1.3 Market Scope
1.3.1 Markets Covered
1.3.2 Years Considered
1.4 Currency
1.5 Limitations
1.6 Stakeholders
2 Research Methodology (Page No. - 17)
2.1 Research Data
2.1.1 Secondary Data
2.1.1.1 Key Data From Secondary Sources
2.1.2 Primary Data
2.1.2.1 Key Data From Primary Sources
2.1.2.2 Key Industry Insights
2.1.2.3 Breakdown of Primary Interviews
2.2 Market Size Estimation
2.2.1 Bottom-Up Approach
2.2.2 Top-Down Approach
2.3 Market Breakdown and Data Triangulation
2.4 Research Assumptions
2.4.1 Assumptions
3 Executive Summary (Page No. - 25)
4 Premium Insights (Page No. - 29)
4.1 Attractive Market Opportunities in the NLP in Healthcare and Life Sciences Market
4.2 Global Market – By Type
4.3 Global NLP Healthcare Market
4.4 Lifecycle Analysis, By Region 2016
4.5 Market Potential
4.6 NLP in Healthcare and Life Sciences: Region Wise Adoption Scenario
5 NLP in Healthcare and Life Sciences Market Overview (Page No. - 33)
5.1 Introduction
5.2 Market Segmentation
5.3 Market Segmentation
5.3.1 By Component
5.3.2 By Type
5.3.3 By Application
5.3.4 By Deployment Mode
5.3.5 By Region
5.4 Market Dynamics
5.4.1 Drivers
5.4.1.1 Huge Surge in Clinical Data
5.4.1.2 Increase in the Use of Connected Devices
5.4.1.3 Evolving Consumer Needs
5.4.2 Restraints
5.4.2.1 Limited Access to Clinical Data
5.4.2.2 Lack of Institutional Commitment
5.4.3 Opportunities
5.4.3.1 Government Policies and Initiatives
5.4.3.2 Integration of Social Media for Assessing Population Health
5.4.4 Challenges
5.4.4.1 Unstructured Clinical Notes and Text
6 NLP in Healthcare and Life Sciences Market : Industry Trends (Page No. - 41)
6.1 Introduction
6.2 Evolution
6.3 Value Chain Analysis
6.4 Strategic Benchmarking
7 Market, By Component (Page No. - 45)
7.1 Introduction
7.2 Technology
7.2.1 Interactive Voice Response
7.2.2 Optical Character Recognition
7.2.3 Pattern and Image Recognition
7.2.4 Auto Coding
7.2.5 Classification and Categorization
7.2.6 Text Analytics
7.2.7 Speech Analytics
7.3 Services
7.3.1 Professional Services
7.3.2 Support and Maintenance Services
8 NLP in Healthcare and Life Sciences Market By Type (Page No. - 56)
8.1 Introduction
8.2 Rule-Based NLP
8.3 Statistical-Based NLP
8.4 Hybrid NLP
9 Market By Application (Page No. - 61)
9.1 Introduction
9.2 Predictive Risk Analytics
9.3 Machine Translation
9.4 Information Extraction
9.5 Report Generation
9.6 Others
10 NLP in Healthcare and Life Sciences Market, By Deployment Mode (Page No. - 67)
10.1 Introduction
10.2 On-Premise
10.3 Cloud
11 Geographic Analysis (Page No. - 71)
11.1 Introduction
11.2 North America
11.2.1 U.S.
11.2.2 Canada
11.3 Europe
11.3.1 U.K.
11.3.2 Germany
11.3.3 France
11.3.4 Rest of Europe
11.4 Asia-Pacific (APAC)
11.4.1 China
11.4.2 Japan
11.4.3 Korea
11.4.4 Rest of Asia-Pacific
11.5 Middle East and Africa
11.5.1 Middle East
11.5.2 Africa
11.6 Latin America
11.6.1 Brazil
11.6.2 Mexico
11.6.3 Rest of Latin America
12 Competitive Landscape (Page No. - 95)
12.1 Introduction
12.2 Competitive Situation and Trends
12.2.1 New Product Launches and Enhancements
12.2.2 Partnerships, Agreements, and Collaborations
12.2.3 Mergers and Acquisitions
12.2.4 Integrations and Expansions
13 Company Profiles (Page No. - 101)
(Overview, Products & Services, Strategies & Insights, Developments and MnM View)*
13.1 Introduction
13.2 3M
13.3 Cerner Corporation
13.4 IBM Corporation
13.5 Microsoft Corporation
13.6 Nuance Communications, Inc.
13.7 Heath Fidelity
13.8 Linguamatics
13.9 Dolbey Systems, Inc.
13.10 Apixio
13.11 Mmodal IP PLC
13.12 Clinithink Inc.
*Details on Overview, Products & Services, Strategies & Insights, Developments and MnM View Might Not Be Captured in Case of Unlisted Companies.
14 Appendix (Page No. - 128)
14.1 Industry Experts
14.2 Discussion Guide
14.3 Knowledge Store: Marketsandmarkets’ Subscription Portal
14.4 Introducing RT: Real-Time Market Intelligence
14.5 Related Reports
List of Tables (66 Tables)
Table 1 Global NLP in Healthcare and Life Sciences Market Size and Growth Rate, 2014-2021 (USD Million) (Y-O-Y %)
Table 2 Market Size, By Component, 2014-2021 (USD Million)
Table 3 Market Size, By Technology, 2014-2021 (USD Million)
Table 4 Interactive Voice Response: Market Size, By Region, 2014-2021 (USD Million)
Table 5 Optical Character Recognition: Market Size, By Region, 2014-2021 (USD Million)
Table 6 Pattern and Image Recognition: Market Size, By Region, 2014-2021 (USD Million)
Table 7 Auto Coding: Market Size, By Region, 2014-2021 (USD Million)
Table 8 Classification and Categorization: Market Size, By Region, 2014-2021 (USD Million)
Table 9 Text Analytics: Market Size, By Region, 2014-2021 (USD Million)
Table 10 Speech Analytics: Market Size, By Region, 2014-2021 (USD Million)
Table 11 NLP in Healthcare and Life Sciences Market Size, By Service, 2014-2021 (USD Million)
Table 12 Professional Services: Market Size, By Region, 2014-2021 (USD Million)
Table 13 Support and Maintenance Services: Market Size, By Region, 2014-2021 (USD Million)
Table 14 NLP in Healthcare and Life Sciences Market Size, By Type, 2014-2021 (USD Million)
Table 15 Rule Based: Market Size, By Region, 2014-2021 (USD Million)
Table 16 Statistical-Based: Market Size, By Region, 2014-2021 (USD Million)
Table 17 Hybrid NLP: Market Size, By Region, 2014-2021 (USD Million)
Table 18 NLP in Healthcare and Life Sciences Market Size, By Application, 2014-2021 (USD Million)
Table 19 Predictive Risk Analytics: Market Size, By Region, 2014-2021 (USD Million)
Table 20 Machine Translation: Market Size, By Region, 2014-2021 (USD Million)
Table 21 Information Extraction: NLP Healthcare Market Size, By Region, 2014-2021 (USD Million)
Table 22 Report Generation: Market Size, By Region, 2014-2021 (USD Million)
Table 23 Others: Market Size, By Region, 2014-2021 (USD Million)
Table 24 NLP in Healthcare and Life Sciences Market Size, By Deployment Mode, 2014-2021 (USD Million)
Table 25 On-Premise: Market Size, By Region, 2014-2021 (USD Million)
Table 26 Cloud: Market Size, By Region, 2014-2021 (USD Million)
Table 27 Natural Language Processing in Healthcare and Life Sciences Market Size, By Region, 2014-2021 (USD Million)
Table 28 North America: Natural Language Processing in Healthcare and Life Sciences Market Size, By Country, 2014-2021 (USD Million)
Table 29 North America: NLP in Healthcare and Life Sciences Market Size, By Component, 2014-2021 (USD Million)
Table 30 North America: Market Size, By Technology, 2014-2021 (USD Million)
Table 31 North America: Market Size, By Service, 2014-2021 (USD Million)
Table 32 North America: Market Size, By Type, 2014-2021 (USD Million)
Table 33 North America: Market Size, By Application, 2014-2021 (USD Million)
Table 34 North America: Market Size, By Deployment Mode, 2014-2021 (USD Million)
Table 35 Europe: NLP in Healthcare and Life Sciences Market Size, By Country, 2014-2021 (USD Million)
Table 36 Europe: Market Size, By Component, 2014-2021 (USD Million)
Table 37 Europe: Market Size, By Technology, 2014-2021 (USD Million)
Table 38 Europe: Market Size, By Service, 2014-2021 (USD Million)
Table 39 Europe: Market Size, By Type, 2014-2021 (USD Million)
Table 40 Europe: Market Size, By Application, 2014-2021 (USD Million)
Table 41 Europe: Market Size, By Deployment Mode, 2014-2021 (USD Million)
Table 42 Asia-Pacific: Market Size, By Country, 2014-2021 (USD Million)
Table 43 Asia-Pacific: NLP in Healthcare and Life Sciences Market Size, By Component, 2014-2021 (USD Million)
Table 44 Asia-Pacific: Market Size, By Technology, 2014-2021 (USD Million)
Table 45 Asia-Pacific: Market Size, By Service, 2014-2021 (USD Million)
Table 46 Asia-Pacific: Market Size, By Type, 2014-2021 (USD Million)
Table 47 Asia-Pacific: Market Size, By Application, 2014-2021 (USD Million)
Table 48 Asia-Pacific: Market Size, By Deployment Mode, 2014-2021 (USD Million)
Table 49 Middle East & Africa: Market Size, By Country, 2014-2021 (USD Million)
Table 50 Middle East & Africa: NLP Healthcare Market Size, By Component, 2014-2021 (USD Million)
Table 51 Middle East & Africa: Market Size, By Technology, 2014-2021 (USD Million)
Table 52 Middle East & Africa: Market Size, By Service, 2014-2021 (USD Million)
Table 53 Middle East & Africa: Market Size, By Type, 2014-2021 (USD Million)
Table 54 Middle East & Africa: Market Size, By Application, 2014-2021 (USD Million)
Table 55 Middle East & Africa: Market Size, By Deployment Mode, 2014-2021 (USD Million)
Table 56 Latin America: NLP in Healthcare and Life Sciences Market Size, By Country, 2014-2021 (USD Million)
Table 57 Latin America: Market Size, By Component, 2014-2021 (USD Million)
Table 58 Latin America: Market Size, By Technology, 2014-2021 (USD Million)
Table 59 Latin America: Market Size, By Service, 2014-2021 (USD Million)
Table 60 Latin America: Market Size, By Type, 2014-2021 (USD Million)
Table 61 Latin America: Market Size, By Application, 2014-2021 (USD Million)
Table 62 Latin America: NLP in Healthcare and Life Sciences Market Size, By Deployment Mode, 2014-2021 (USD Million)
Table 63 New Product Launches and Enhancements, 2013-2016
Table 64 Partnerships, Agreements, and Collaborations, 2013-2016
Table 65 Mergers and Acquisitions, 2014-2016
Table 66 Integrations and Expansions, 2014-2016
List of Figures (46 Figures)
Figure 1 Global NLP in Healthcare and Life Sciences Market : Research Design
Figure 2 Global Market: Research Design
Figure 3 Market Size Estimation Methodology: Bottom-Up Approach
Figure 4 Market Size Estimation Methodology: Top-Down Approach
Figure 5 Data Triangulation
Figure 6 Market Size, By Technology (2016 & 2021): Pattern and Image Recognition is Expected to Witness the Highest CAGR
Figure 7 Market Size, By Application (2016 & 2021): Report Generation is Expected to Have the Highest CAGR
Figure 8 Market Size, By Type (2016 & 2021): Statistical NLP is Expected to Lead the NLP in Healthcare and Life Sciences Market
Figure 9 Market Share, By Deployment Mode (2016): Cloud Deployment is Expected to Witness Higher CAGR
Figure 10 Global Market Share – North America is Estimated to Hold the Largest Market Share in 2016
Figure 11 Hybrid NLP in Expected to Grow at the Highest CAGR During the Forecast Period
Figure 12 North America is Estimated to Hold the Maximum Share in the Market (2016)
Figure 13 Regional Lifecycle – North America Expected to Grow With the Highest CAGR During the Forecast Period
Figure 14 North America is Expected to Have the Highest Growth Potential During the Forecast Period
Figure 15 APAC Market is Expected to Grow Faster as Compared to Other Regions During the Forecast Period
Figure 16 NLP Healthcare Market Segmentation
Figure 17 Market Segmentation: By Component
Figure 18 NLP in Healthcare and Life Sciences Segmentation: By Type
Figure 19 Market Segmentation: By Application
Figure 20 Market Segmentation: By Deployment Mode
Figure 21 Market Segmentation: By Region
Figure 22 Drivers, Restraints, Opportunities, and Challenges of the NLP in Healthcare and Life Sciences Market
Figure 23 NLP Healthcare Market: Value Chain Analysis
Figure 24 Strategic Benchmarking: New Product Launches and Enhancements is the Key Growth Strategy Adopted By Key Market Players From 2014 to 2016
Figure 25 Technology Segment is Expected to Grow at A Higher CAGR During the Forecast Period
Figure 26 Pattern and Image Recognition is Expected to Grow at the Highest CAGR During the Forecast Period
Figure 27 Professional Services is Expected to Grow at A Higher CAGR During the Forecast Period
Figure 28 Statistical-Based NLP Going to Exibit the Highest Growth Rate for the Forecast Period
Figure 29 Report Generation Application Segment is Expected to Grow at the Highest CAGR During the Forecast Period
Figure 30 Cloud Deployment is Expected to Grow With the Highest Market Share During the Forecast Period
Figure 31 North America is Projected to Exhibit the Highest Growth Rate in the Market
Figure 32 Geographic Snapshot: North America is Estimated to Account for the Highest CAGR in the NLP Healthcare Market
Figure 33 North America Snapshot
Figure 34 Companies Adopted New Product Launch and Enhancement as the Key Growth Strategy Over the Last Three Years
Figure 35 Market Evaluation Framework
Figure 36 Battle for Market Share: New Product Launch and Enhancement Was the Key Growth Strategy of the Market
Figure 37 Geographic Revenue Mix of Top 5 Players
Figure 38 3M : Company Snapshot
Figure 39 3M : SWOT Analysis
Figure 40 Cerner Corporation: Company Snapshot
Figure 41 IBM Corporation: Company Snapshot
Figure 42 IBM Corporation : SWOT Analysis
Figure 43 Microsoft Corporation: Company Snapshot
Figure 44 Microsoft Corporation : SWOT Analysis
Figure 45 Nuance Communications, Inc. : Company Snapshot
Figure 46 Nuance Communications, Inc.: SWOT Analysis
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