Global Healthcare Natural Language Processing research
Global Healthcare Natural Language Processing research

Healthcare Natural Language Processing Comprehensive Study by Type (Machine Translation, Information Extraction, Automatic Summarization, Text and Voice Processing), Application (Interactive Voice Response (IVR), Pattern and Image Recognition, Auto Coding, Classification and Categorization, Text and Speech Analytics, Others), Technology (Rule-based NLP, Statistical NLP, Hybrid NLP), End-User (Hospitals, Clinics, Others) Players and Region - Global Market Outlook to 2026

Healthcare Natural Language Processing Market Segmented into XX Submarkets. | Forecast Years: 2021- 2026  

Oct 2021 Edition 226 Pages 166 Tables & Figures
  • Summary
  • Market Segments
  • Table of Content
  • List of Tables & Figures
  • Companies Mentioned
What is Healthcare Natural Language Processing Market Scope?
Natural language processing, also known as NLP, is a human-computer interface that analyses, processes, and outputs computational linguistics based on human language. NLP technology enables humans to communicate with computers in meaningful ways using natural languages such as German or English rather than artificial computer languages such as C++ or Java. The use of NLP technology in the worldwide healthcare industry is on the rise right now. Several public and commercial healthcare service providers, including clinics and well-known hospitals, are using natural language processing (NLP) technology in clinical applications to increase patient involvement and overall decision making. The significant increase in the volume of disorganized clinical information is driving the healthcare natural language processing industry. The growing use of EHR (electronic health records) systems in the worldwide healthcare business are resulting in the development of massive amounts of clinical data, which includes patient information, diagnosis procedures, and other pertinent information such as medication details. Furthermore, the integration of NLP technology with computer apps assists these healthcare service providers in improving patient and family interaction.

The Healthcare Natural Language Processing market study is being classified by Type (Machine Translation, Information Extraction, Automatic Summarization and Text and Voice Processing), by Application (Interactive Voice Response (IVR), Pattern and Image Recognition, Auto Coding, Classification and Categorization, Text and Speech Analytics and Others) and major geographies with country level break-up.

The companies are exploring the market by adopting mergers & acquisitions, expansions, investments, new service launches and collaborations as their preferred strategies. The players are exploring new geographies through expansions and acquisitions to avail a competitive advantage through combined synergies. Analysts at AMA predicts that Players from United States will contribute to the maximum growth of Global Healthcare Natural Language Processing market throughout the predicted period.

3M (United States), Cerner (United States), Nuance (United States), Health Fidelity (United States), Dolbey (United States), Microsoft (United States), IBM (United States), Google (United States), AWS (United States), Apixio (United States), Averbis (Germany) and Linguamatics (United Kingdom) are some of the key players profiled in the study.

Segmentation Analysis
Analyst at AMA have segmented the market study of Global Healthcare Natural Language Processing market by Type, Application and Region.

On the basis of geography, the market of Healthcare Natural Language Processing has been segmented into South America (Brazil, Argentina, Rest of South America), Asia Pacific (China, Japan, India, South Korea, Taiwan, Australia, Rest of Asia-Pacific), Europe (Germany, France, Italy, United Kingdom, Netherlands, Rest of Europe), MEA (Middle East, Africa), North America (United States, Canada, Mexico).

November 2020 Ė Google Launches Healthcare Natural Language API and AutoML Entity Extraction for Healthcare


Influencing Market Trend
  • Ability to Analyze and Extract Meaning from Narrative Text and non-Related Data Sources

Market Drivers
  • Rising Urge of Predictive Analytics to Reduce Risk and Improve Significant Health Concerns
  • Growing Demand for IMPROVING EHR Data Usability to Better Patient Care

Opportunities
  • Ensemble of NLP Systems to Boost Phenotyping Capabilities
  • Rising Demand for NLP Systems Programmed to Understand the Context of Medical Records

Restraints
  • Specific Medical Sub-Languages and Poor Input Data Quality

Challenges
  • Data Security and Privacy Concerns


Key Target Audience
Software Providers, Healthcare Industry, Network Providers and Others

Customization available in this Study:
The Study can be customized to meet your requirements. Please connect with our representative, who will ensure you get a report that suits your needs.

To compete effectively, companies also require quantitative estimates of the future growth and qualitative nature of the market. AMA Research features not just specific market sizing estimates, but also include significant value-added commentary on Technological Trends and Innovations, Regulatory Policies, Market Maturity Indicators, Market Share Movements, New Entrants into the Market & Entry/Exit Barriers, Consumer Demographics, Supporting Company Financial and Cash Flow Planning, Open Up New Markets , To Seize Powerful Market Opportunities, Key Decision in Planning and to Further Expand Market Share, Identify Key Business Segments, Market Proposition & Gap Analysis.

Frequently Asked Questions (FAQ):

1. At what growth rate would the Healthcare Natural Language Processing market expands?
The Global Healthcare Natural Language Processing market is expected to see a growth of % during projected year 2020 to 2026.

2. Who are the prominent players of the Global Healthcare Natural Language Processing market?
The prominent players of Global Healthcare Natural Language Processing market are 3M (United States), Cerner (United States), Nuance (United States), Health Fidelity (United States), Dolbey (United States), Microsoft (United States), IBM (United States), Google (United States), AWS (United States), Apixio (United States), Averbis (Germany) and Linguamatics (United Kingdom), to name a few.

3. What are the top priorities to focus for Healthcare Natural Language Processing marketís growth?
In this highly competitive & fast evolving Healthcare Natural Language Processing industry, the top strategic priorities would remain consistent like innovation, R&D and M&A.
Report Objectives / Segmentation Covered
By Type
  • Machine Translation
  • Information Extraction
  • Automatic Summarization
  • Text and Voice Processing
By Application
  • Interactive Voice Response (IVR)
  • Pattern and Image Recognition
  • Auto Coding
  • Classification and Categorization
  • Text and Speech Analytics
  • Others
By Technology
  • Rule-based NLP
  • Statistical NLP
  • Hybrid NLP

By End-User
  • Hospitals
  • Clinics
  • Others

By Regions
  • South America
    • Brazil
    • Argentina
    • Rest of South America
  • Asia Pacific
    • China
    • Japan
    • India
    • South Korea
    • Taiwan
    • Australia
    • Rest of Asia-Pacific
  • Europe
    • Germany
    • France
    • Italy
    • United Kingdom
    • Netherlands
    • Rest of Europe
  • MEA
    • Middle East
    • Africa
  • North America
    • United States
    • Canada
    • Mexico
  • 1. Market Overview
    • 1.1. Introduction
    • 1.2. Scope/Objective of the Study
      • 1.2.1. Research Objective
  • 2. Executive Summary
    • 2.1. Introduction
  • 3. Market Dynamics
    • 3.1. Introduction
    • 3.2. Market Drivers
      • 3.2.1. Rising Urge of Predictive Analytics to Reduce Risk and Improve Significant Health Concerns
      • 3.2.2. Growing Demand for IMPROVING EHR Data Usability to Better Patient Care
    • 3.3. Market Challenges
      • 3.3.1. Data Security and Privacy Concerns
    • 3.4. Market Trends
      • 3.4.1. Ability to Analyze and Extract Meaning from Narrative Text and non-Related Data Sources
  • 4. Market Factor Analysis
    • 4.1. Porters Five Forces
    • 4.2. Supply/Value Chain
    • 4.3. PESTEL analysis
    • 4.4. Market Entropy
    • 4.5. Patent/Trademark Analysis
  • 5. Global Healthcare Natural Language Processing, by Type, Application, Technology, End-User and Region (value and price ) (2015-2020)
    • 5.1. Introduction
    • 5.2. Global Healthcare Natural Language Processing (Value)
      • 5.2.1. Global Healthcare Natural Language Processing by: Type (Value)
        • 5.2.1.1. Machine Translation
        • 5.2.1.2. Information Extraction
        • 5.2.1.3. Automatic Summarization
        • 5.2.1.4. Text and Voice Processing
      • 5.2.2. Global Healthcare Natural Language Processing by: Application (Value)
        • 5.2.2.1. Interactive Voice Response (IVR)
        • 5.2.2.2. Pattern and Image Recognition
        • 5.2.2.3. Auto Coding
        • 5.2.2.4. Classification and Categorization
        • 5.2.2.5. Text and Speech Analytics
        • 5.2.2.6. Others
      • 5.2.3. Global Healthcare Natural Language Processing by: Technology (Value)
        • 5.2.3.1. Rule-based NLP
        • 5.2.3.2. Statistical NLP
        • 5.2.3.3. Hybrid NLP
      • 5.2.4. Global Healthcare Natural Language Processing by: End-User (Value)
        • 5.2.4.1. Hospitals
        • 5.2.4.2. Clinics
        • 5.2.4.3. Others
      • 5.2.5. Global Healthcare Natural Language Processing Region
        • 5.2.5.1. South America
          • 5.2.5.1.1. Brazil
          • 5.2.5.1.2. Argentina
          • 5.2.5.1.3. Rest of South America
        • 5.2.5.2. Asia Pacific
          • 5.2.5.2.1. China
          • 5.2.5.2.2. Japan
          • 5.2.5.2.3. India
          • 5.2.5.2.4. South Korea
          • 5.2.5.2.5. Taiwan
          • 5.2.5.2.6. Australia
          • 5.2.5.2.7. Rest of Asia-Pacific
        • 5.2.5.3. Europe
          • 5.2.5.3.1. Germany
          • 5.2.5.3.2. France
          • 5.2.5.3.3. Italy
          • 5.2.5.3.4. United Kingdom
          • 5.2.5.3.5. Netherlands
          • 5.2.5.3.6. Rest of Europe
        • 5.2.5.4. MEA
          • 5.2.5.4.1. Middle East
          • 5.2.5.4.2. Africa
        • 5.2.5.5. North America
          • 5.2.5.5.1. United States
          • 5.2.5.5.2. Canada
          • 5.2.5.5.3. Mexico
    • 5.3. Global Healthcare Natural Language Processing (Price)
      • 5.3.1. Global Healthcare Natural Language Processing by: Type (Price)
  • 6. Healthcare Natural Language Processing: Manufacturers/Players Analysis
    • 6.1. Competitive Landscape
      • 6.1.1. Market Share Analysis
        • 6.1.1.1. Top 3
        • 6.1.1.2. Top 5
    • 6.2. Peer Group Analysis (2020)
    • 6.3. BCG Matrix
    • 6.4. Company Profile
      • 6.4.1. 3M (United States)
        • 6.4.1.1. Business Overview
        • 6.4.1.2. Products/Services Offerings
        • 6.4.1.3. Financial Analysis
        • 6.4.1.4. SWOT Analysis
      • 6.4.2. Cerner (United States)
        • 6.4.2.1. Business Overview
        • 6.4.2.2. Products/Services Offerings
        • 6.4.2.3. Financial Analysis
        • 6.4.2.4. SWOT Analysis
      • 6.4.3. Nuance (United States)
        • 6.4.3.1. Business Overview
        • 6.4.3.2. Products/Services Offerings
        • 6.4.3.3. Financial Analysis
        • 6.4.3.4. SWOT Analysis
      • 6.4.4. Health Fidelity (United States)
        • 6.4.4.1. Business Overview
        • 6.4.4.2. Products/Services Offerings
        • 6.4.4.3. Financial Analysis
        • 6.4.4.4. SWOT Analysis
      • 6.4.5. Dolbey (United States)
        • 6.4.5.1. Business Overview
        • 6.4.5.2. Products/Services Offerings
        • 6.4.5.3. Financial Analysis
        • 6.4.5.4. SWOT Analysis
      • 6.4.6. Microsoft (United States)
        • 6.4.6.1. Business Overview
        • 6.4.6.2. Products/Services Offerings
        • 6.4.6.3. Financial Analysis
        • 6.4.6.4. SWOT Analysis
      • 6.4.7. IBM (United States)
        • 6.4.7.1. Business Overview
        • 6.4.7.2. Products/Services Offerings
        • 6.4.7.3. Financial Analysis
        • 6.4.7.4. SWOT Analysis
      • 6.4.8. Google (United States)
        • 6.4.8.1. Business Overview
        • 6.4.8.2. Products/Services Offerings
        • 6.4.8.3. Financial Analysis
        • 6.4.8.4. SWOT Analysis
      • 6.4.9. AWS (United States)
        • 6.4.9.1. Business Overview
        • 6.4.9.2. Products/Services Offerings
        • 6.4.9.3. Financial Analysis
        • 6.4.9.4. SWOT Analysis
      • 6.4.10. Apixio (United States)
        • 6.4.10.1. Business Overview
        • 6.4.10.2. Products/Services Offerings
        • 6.4.10.3. Financial Analysis
        • 6.4.10.4. SWOT Analysis
      • 6.4.11. Averbis (Germany)
        • 6.4.11.1. Business Overview
        • 6.4.11.2. Products/Services Offerings
        • 6.4.11.3. Financial Analysis
        • 6.4.11.4. SWOT Analysis
      • 6.4.12. Linguamatics (United Kingdom)
        • 6.4.12.1. Business Overview
        • 6.4.12.2. Products/Services Offerings
        • 6.4.12.3. Financial Analysis
        • 6.4.12.4. SWOT Analysis
  • 7. Global Healthcare Natural Language Processing Sale, by Type, Application, Technology, End-User and Region (value and price ) (2021-2026)
    • 7.1. Introduction
    • 7.2. Global Healthcare Natural Language Processing (Value)
      • 7.2.1. Global Healthcare Natural Language Processing by: Type (Value)
        • 7.2.1.1. Machine Translation
        • 7.2.1.2. Information Extraction
        • 7.2.1.3. Automatic Summarization
        • 7.2.1.4. Text and Voice Processing
      • 7.2.2. Global Healthcare Natural Language Processing by: Application (Value)
        • 7.2.2.1. Interactive Voice Response (IVR)
        • 7.2.2.2. Pattern and Image Recognition
        • 7.2.2.3. Auto Coding
        • 7.2.2.4. Classification and Categorization
        • 7.2.2.5. Text and Speech Analytics
        • 7.2.2.6. Others
      • 7.2.3. Global Healthcare Natural Language Processing by: Technology (Value)
        • 7.2.3.1. Rule-based NLP
        • 7.2.3.2. Statistical NLP
        • 7.2.3.3. Hybrid NLP
      • 7.2.4. Global Healthcare Natural Language Processing by: End-User (Value)
        • 7.2.4.1. Hospitals
        • 7.2.4.2. Clinics
        • 7.2.4.3. Others
      • 7.2.5. Global Healthcare Natural Language Processing Region
        • 7.2.5.1. South America
          • 7.2.5.1.1. Brazil
          • 7.2.5.1.2. Argentina
          • 7.2.5.1.3. Rest of South America
        • 7.2.5.2. Asia Pacific
          • 7.2.5.2.1. China
          • 7.2.5.2.2. Japan
          • 7.2.5.2.3. India
          • 7.2.5.2.4. South Korea
          • 7.2.5.2.5. Taiwan
          • 7.2.5.2.6. Australia
          • 7.2.5.2.7. Rest of Asia-Pacific
        • 7.2.5.3. Europe
          • 7.2.5.3.1. Germany
          • 7.2.5.3.2. France
          • 7.2.5.3.3. Italy
          • 7.2.5.3.4. United Kingdom
          • 7.2.5.3.5. Netherlands
          • 7.2.5.3.6. Rest of Europe
        • 7.2.5.4. MEA
          • 7.2.5.4.1. Middle East
          • 7.2.5.4.2. Africa
        • 7.2.5.5. North America
          • 7.2.5.5.1. United States
          • 7.2.5.5.2. Canada
          • 7.2.5.5.3. Mexico
    • 7.3. Global Healthcare Natural Language Processing (Price)
      • 7.3.1. Global Healthcare Natural Language Processing by: Type (Price)
  • 8. Appendix
    • 8.1. Acronyms
  • 9. Methodology and Data Source
    • 9.1. Methodology/Research Approach
      • 9.1.1. Research Programs/Design
      • 9.1.2. Market Size Estimation
      • 9.1.3. Market Breakdown and Data Triangulation
    • 9.2. Data Source
      • 9.2.1. Secondary Sources
      • 9.2.2. Primary Sources
    • 9.3. Disclaimer
List of Tables
  • Table 1. Healthcare Natural Language Processing: by Type(USD Million)
  • Table 2. Healthcare Natural Language Processing Machine Translation , by Region USD Million (2015-2020)
  • Table 3. Healthcare Natural Language Processing Information Extraction , by Region USD Million (2015-2020)
  • Table 4. Healthcare Natural Language Processing Automatic Summarization , by Region USD Million (2015-2020)
  • Table 5. Healthcare Natural Language Processing Text and Voice Processing , by Region USD Million (2015-2020)
  • Table 6. Healthcare Natural Language Processing: by Application(USD Million)
  • Table 7. Healthcare Natural Language Processing Interactive Voice Response (IVR) , by Region USD Million (2015-2020)
  • Table 8. Healthcare Natural Language Processing Pattern and Image Recognition , by Region USD Million (2015-2020)
  • Table 9. Healthcare Natural Language Processing Auto Coding , by Region USD Million (2015-2020)
  • Table 10. Healthcare Natural Language Processing Classification and Categorization , by Region USD Million (2015-2020)
  • Table 11. Healthcare Natural Language Processing Text and Speech Analytics , by Region USD Million (2015-2020)
  • Table 12. Healthcare Natural Language Processing Others , by Region USD Million (2015-2020)
  • Table 13. Healthcare Natural Language Processing: by Technology(USD Million)
  • Table 14. Healthcare Natural Language Processing Rule-based NLP , by Region USD Million (2015-2020)
  • Table 15. Healthcare Natural Language Processing Statistical NLP , by Region USD Million (2015-2020)
  • Table 16. Healthcare Natural Language Processing Hybrid NLP , by Region USD Million (2015-2020)
  • Table 17. Healthcare Natural Language Processing: by End-User(USD Million)
  • Table 18. Healthcare Natural Language Processing Hospitals , by Region USD Million (2015-2020)
  • Table 19. Healthcare Natural Language Processing Clinics , by Region USD Million (2015-2020)
  • Table 20. Healthcare Natural Language Processing Others , by Region USD Million (2015-2020)
  • Table 21. South America Healthcare Natural Language Processing, by Country USD Million (2015-2020)
  • Table 22. South America Healthcare Natural Language Processing, by Type USD Million (2015-2020)
  • Table 23. South America Healthcare Natural Language Processing, by Application USD Million (2015-2020)
  • Table 24. South America Healthcare Natural Language Processing, by Technology USD Million (2015-2020)
  • Table 25. South America Healthcare Natural Language Processing, by End-User USD Million (2015-2020)
  • Table 26. Brazil Healthcare Natural Language Processing, by Type USD Million (2015-2020)
  • Table 27. Brazil Healthcare Natural Language Processing, by Application USD Million (2015-2020)
  • Table 28. Brazil Healthcare Natural Language Processing, by Technology USD Million (2015-2020)
  • Table 29. Brazil Healthcare Natural Language Processing, by End-User USD Million (2015-2020)
  • Table 30. Argentina Healthcare Natural Language Processing, by Type USD Million (2015-2020)
  • Table 31. Argentina Healthcare Natural Language Processing, by Application USD Million (2015-2020)
  • Table 32. Argentina Healthcare Natural Language Processing, by Technology USD Million (2015-2020)
  • Table 33. Argentina Healthcare Natural Language Processing, by End-User USD Million (2015-2020)
  • Table 34. Rest of South America Healthcare Natural Language Processing, by Type USD Million (2015-2020)
  • Table 35. Rest of South America Healthcare Natural Language Processing, by Application USD Million (2015-2020)
  • Table 36. Rest of South America Healthcare Natural Language Processing, by Technology USD Million (2015-2020)
  • Table 37. Rest of South America Healthcare Natural Language Processing, by End-User USD Million (2015-2020)
  • Table 38. Asia Pacific Healthcare Natural Language Processing, by Country USD Million (2015-2020)
  • Table 39. Asia Pacific Healthcare Natural Language Processing, by Type USD Million (2015-2020)
  • Table 40. Asia Pacific Healthcare Natural Language Processing, by Application USD Million (2015-2020)
  • Table 41. Asia Pacific Healthcare Natural Language Processing, by Technology USD Million (2015-2020)
  • Table 42. Asia Pacific Healthcare Natural Language Processing, by End-User USD Million (2015-2020)
  • Table 43. China Healthcare Natural Language Processing, by Type USD Million (2015-2020)
  • Table 44. China Healthcare Natural Language Processing, by Application USD Million (2015-2020)
  • Table 45. China Healthcare Natural Language Processing, by Technology USD Million (2015-2020)
  • Table 46. China Healthcare Natural Language Processing, by End-User USD Million (2015-2020)
  • Table 47. Japan Healthcare Natural Language Processing, by Type USD Million (2015-2020)
  • Table 48. Japan Healthcare Natural Language Processing, by Application USD Million (2015-2020)
  • Table 49. Japan Healthcare Natural Language Processing, by Technology USD Million (2015-2020)
  • Table 50. Japan Healthcare Natural Language Processing, by End-User USD Million (2015-2020)
  • Table 51. India Healthcare Natural Language Processing, by Type USD Million (2015-2020)
  • Table 52. India Healthcare Natural Language Processing, by Application USD Million (2015-2020)
  • Table 53. India Healthcare Natural Language Processing, by Technology USD Million (2015-2020)
  • Table 54. India Healthcare Natural Language Processing, by End-User USD Million (2015-2020)
  • Table 55. South Korea Healthcare Natural Language Processing, by Type USD Million (2015-2020)
  • Table 56. South Korea Healthcare Natural Language Processing, by Application USD Million (2015-2020)
  • Table 57. South Korea Healthcare Natural Language Processing, by Technology USD Million (2015-2020)
  • Table 58. South Korea Healthcare Natural Language Processing, by End-User USD Million (2015-2020)
  • Table 59. Taiwan Healthcare Natural Language Processing, by Type USD Million (2015-2020)
  • Table 60. Taiwan Healthcare Natural Language Processing, by Application USD Million (2015-2020)
  • Table 61. Taiwan Healthcare Natural Language Processing, by Technology USD Million (2015-2020)
  • Table 62. Taiwan Healthcare Natural Language Processing, by End-User USD Million (2015-2020)
  • Table 63. Australia Healthcare Natural Language Processing, by Type USD Million (2015-2020)
  • Table 64. Australia Healthcare Natural Language Processing, by Application USD Million (2015-2020)
  • Table 65. Australia Healthcare Natural Language Processing, by Technology USD Million (2015-2020)
  • Table 66. Australia Healthcare Natural Language Processing, by End-User USD Million (2015-2020)
  • Table 67. Rest of Asia-Pacific Healthcare Natural Language Processing, by Type USD Million (2015-2020)
  • Table 68. Rest of Asia-Pacific Healthcare Natural Language Processing, by Application USD Million (2015-2020)
  • Table 69. Rest of Asia-Pacific Healthcare Natural Language Processing, by Technology USD Million (2015-2020)
  • Table 70. Rest of Asia-Pacific Healthcare Natural Language Processing, by End-User USD Million (2015-2020)
  • Table 71. Europe Healthcare Natural Language Processing, by Country USD Million (2015-2020)
  • Table 72. Europe Healthcare Natural Language Processing, by Type USD Million (2015-2020)
  • Table 73. Europe Healthcare Natural Language Processing, by Application USD Million (2015-2020)
  • Table 74. Europe Healthcare Natural Language Processing, by Technology USD Million (2015-2020)
  • Table 75. Europe Healthcare Natural Language Processing, by End-User USD Million (2015-2020)
  • Table 76. Germany Healthcare Natural Language Processing, by Type USD Million (2015-2020)
  • Table 77. Germany Healthcare Natural Language Processing, by Application USD Million (2015-2020)
  • Table 78. Germany Healthcare Natural Language Processing, by Technology USD Million (2015-2020)
  • Table 79. Germany Healthcare Natural Language Processing, by End-User USD Million (2015-2020)
  • Table 80. France Healthcare Natural Language Processing, by Type USD Million (2015-2020)
  • Table 81. France Healthcare Natural Language Processing, by Application USD Million (2015-2020)
  • Table 82. France Healthcare Natural Language Processing, by Technology USD Million (2015-2020)
  • Table 83. France Healthcare Natural Language Processing, by End-User USD Million (2015-2020)
  • Table 84. Italy Healthcare Natural Language Processing, by Type USD Million (2015-2020)
  • Table 85. Italy Healthcare Natural Language Processing, by Application USD Million (2015-2020)
  • Table 86. Italy Healthcare Natural Language Processing, by Technology USD Million (2015-2020)
  • Table 87. Italy Healthcare Natural Language Processing, by End-User USD Million (2015-2020)
  • Table 88. United Kingdom Healthcare Natural Language Processing, by Type USD Million (2015-2020)
  • Table 89. United Kingdom Healthcare Natural Language Processing, by Application USD Million (2015-2020)
  • Table 90. United Kingdom Healthcare Natural Language Processing, by Technology USD Million (2015-2020)
  • Table 91. United Kingdom Healthcare Natural Language Processing, by End-User USD Million (2015-2020)
  • Table 92. Netherlands Healthcare Natural Language Processing, by Type USD Million (2015-2020)
  • Table 93. Netherlands Healthcare Natural Language Processing, by Application USD Million (2015-2020)
  • Table 94. Netherlands Healthcare Natural Language Processing, by Technology USD Million (2015-2020)
  • Table 95. Netherlands Healthcare Natural Language Processing, by End-User USD Million (2015-2020)
  • Table 96. Rest of Europe Healthcare Natural Language Processing, by Type USD Million (2015-2020)
  • Table 97. Rest of Europe Healthcare Natural Language Processing, by Application USD Million (2015-2020)
  • Table 98. Rest of Europe Healthcare Natural Language Processing, by Technology USD Million (2015-2020)
  • Table 99. Rest of Europe Healthcare Natural Language Processing, by End-User USD Million (2015-2020)
  • Table 100. MEA Healthcare Natural Language Processing, by Country USD Million (2015-2020)
  • Table 101. MEA Healthcare Natural Language Processing, by Type USD Million (2015-2020)
  • Table 102. MEA Healthcare Natural Language Processing, by Application USD Million (2015-2020)
  • Table 103. MEA Healthcare Natural Language Processing, by Technology USD Million (2015-2020)
  • Table 104. MEA Healthcare Natural Language Processing, by End-User USD Million (2015-2020)
  • Table 105. Middle East Healthcare Natural Language Processing, by Type USD Million (2015-2020)
  • Table 106. Middle East Healthcare Natural Language Processing, by Application USD Million (2015-2020)
  • Table 107. Middle East Healthcare Natural Language Processing, by Technology USD Million (2015-2020)
  • Table 108. Middle East Healthcare Natural Language Processing, by End-User USD Million (2015-2020)
  • Table 109. Africa Healthcare Natural Language Processing, by Type USD Million (2015-2020)
  • Table 110. Africa Healthcare Natural Language Processing, by Application USD Million (2015-2020)
  • Table 111. Africa Healthcare Natural Language Processing, by Technology USD Million (2015-2020)
  • Table 112. Africa Healthcare Natural Language Processing, by End-User USD Million (2015-2020)
  • Table 113. North America Healthcare Natural Language Processing, by Country USD Million (2015-2020)
  • Table 114. North America Healthcare Natural Language Processing, by Type USD Million (2015-2020)
  • Table 115. North America Healthcare Natural Language Processing, by Application USD Million (2015-2020)
  • Table 116. North America Healthcare Natural Language Processing, by Technology USD Million (2015-2020)
  • Table 117. North America Healthcare Natural Language Processing, by End-User USD Million (2015-2020)
  • Table 118. United States Healthcare Natural Language Processing, by Type USD Million (2015-2020)
  • Table 119. United States Healthcare Natural Language Processing, by Application USD Million (2015-2020)
  • Table 120. United States Healthcare Natural Language Processing, by Technology USD Million (2015-2020)
  • Table 121. United States Healthcare Natural Language Processing, by End-User USD Million (2015-2020)
  • Table 122. Canada Healthcare Natural Language Processing, by Type USD Million (2015-2020)
  • Table 123. Canada Healthcare Natural Language Processing, by Application USD Million (2015-2020)
  • Table 124. Canada Healthcare Natural Language Processing, by Technology USD Million (2015-2020)
  • Table 125. Canada Healthcare Natural Language Processing, by End-User USD Million (2015-2020)
  • Table 126. Mexico Healthcare Natural Language Processing, by Type USD Million (2015-2020)
  • Table 127. Mexico Healthcare Natural Language Processing, by Application USD Million (2015-2020)
  • Table 128. Mexico Healthcare Natural Language Processing, by Technology USD Million (2015-2020)
  • Table 129. Mexico Healthcare Natural Language Processing, by End-User USD Million (2015-2020)
  • Table 130. Healthcare Natural Language Processing: by Type(USD/Units)
  • Table 131. Company Basic Information, Sales Area and Its Competitors
  • Table 132. Company Basic Information, Sales Area and Its Competitors
  • Table 133. Company Basic Information, Sales Area and Its Competitors
  • Table 134. Company Basic Information, Sales Area and Its Competitors
  • Table 135. Company Basic Information, Sales Area and Its Competitors
  • Table 136. Company Basic Information, Sales Area and Its Competitors
  • Table 137. Company Basic Information, Sales Area and Its Competitors
  • Table 138. Company Basic Information, Sales Area and Its Competitors
  • Table 139. Company Basic Information, Sales Area and Its Competitors
  • Table 140. Company Basic Information, Sales Area and Its Competitors
  • Table 141. Company Basic Information, Sales Area and Its Competitors
  • Table 142. Company Basic Information, Sales Area and Its Competitors
  • Table 143. Healthcare Natural Language Processing: by Type(USD Million)
  • Table 144. Healthcare Natural Language Processing Machine Translation , by Region USD Million (2021-2026)
  • Table 145. Healthcare Natural Language Processing Information Extraction , by Region USD Million (2021-2026)
  • Table 146. Healthcare Natural Language Processing Automatic Summarization , by Region USD Million (2021-2026)
  • Table 147. Healthcare Natural Language Processing Text and Voice Processing , by Region USD Million (2021-2026)
  • Table 148. Healthcare Natural Language Processing: by Application(USD Million)
  • Table 149. Healthcare Natural Language Processing Interactive Voice Response (IVR) , by Region USD Million (2021-2026)
  • Table 150. Healthcare Natural Language Processing Pattern and Image Recognition , by Region USD Million (2021-2026)
  • Table 151. Healthcare Natural Language Processing Auto Coding , by Region USD Million (2021-2026)
  • Table 152. Healthcare Natural Language Processing Classification and Categorization , by Region USD Million (2021-2026)
  • Table 153. Healthcare Natural Language Processing Text and Speech Analytics , by Region USD Million (2021-2026)
  • Table 154. Healthcare Natural Language Processing Others , by Region USD Million (2021-2026)
  • Table 155. Healthcare Natural Language Processing: by Technology(USD Million)
  • Table 156. Healthcare Natural Language Processing Rule-based NLP , by Region USD Million (2021-2026)
  • Table 157. Healthcare Natural Language Processing Statistical NLP , by Region USD Million (2021-2026)
  • Table 158. Healthcare Natural Language Processing Hybrid NLP , by Region USD Million (2021-2026)
  • Table 159. Healthcare Natural Language Processing: by End-User(USD Million)
  • Table 160. Healthcare Natural Language Processing Hospitals , by Region USD Million (2021-2026)
  • Table 161. Healthcare Natural Language Processing Clinics , by Region USD Million (2021-2026)
  • Table 162. Healthcare Natural Language Processing Others , by Region USD Million (2021-2026)
  • Table 163. South America Healthcare Natural Language Processing, by Country USD Million (2021-2026)
  • Table 164. South America Healthcare Natural Language Processing, by Type USD Million (2021-2026)
  • Table 165. South America Healthcare Natural Language Processing, by Application USD Million (2021-2026)
  • Table 166. South America Healthcare Natural Language Processing, by Technology USD Million (2021-2026)
  • Table 167. South America Healthcare Natural Language Processing, by End-User USD Million (2021-2026)
  • Table 168. Brazil Healthcare Natural Language Processing, by Type USD Million (2021-2026)
  • Table 169. Brazil Healthcare Natural Language Processing, by Application USD Million (2021-2026)
  • Table 170. Brazil Healthcare Natural Language Processing, by Technology USD Million (2021-2026)
  • Table 171. Brazil Healthcare Natural Language Processing, by End-User USD Million (2021-2026)
  • Table 172. Argentina Healthcare Natural Language Processing, by Type USD Million (2021-2026)
  • Table 173. Argentina Healthcare Natural Language Processing, by Application USD Million (2021-2026)
  • Table 174. Argentina Healthcare Natural Language Processing, by Technology USD Million (2021-2026)
  • Table 175. Argentina Healthcare Natural Language Processing, by End-User USD Million (2021-2026)
  • Table 176. Rest of South America Healthcare Natural Language Processing, by Type USD Million (2021-2026)
  • Table 177. Rest of South America Healthcare Natural Language Processing, by Application USD Million (2021-2026)
  • Table 178. Rest of South America Healthcare Natural Language Processing, by Technology USD Million (2021-2026)
  • Table 179. Rest of South America Healthcare Natural Language Processing, by End-User USD Million (2021-2026)
  • Table 180. Asia Pacific Healthcare Natural Language Processing, by Country USD Million (2021-2026)
  • Table 181. Asia Pacific Healthcare Natural Language Processing, by Type USD Million (2021-2026)
  • Table 182. Asia Pacific Healthcare Natural Language Processing, by Application USD Million (2021-2026)
  • Table 183. Asia Pacific Healthcare Natural Language Processing, by Technology USD Million (2021-2026)
  • Table 184. Asia Pacific Healthcare Natural Language Processing, by End-User USD Million (2021-2026)
  • Table 185. China Healthcare Natural Language Processing, by Type USD Million (2021-2026)
  • Table 186. China Healthcare Natural Language Processing, by Application USD Million (2021-2026)
  • Table 187. China Healthcare Natural Language Processing, by Technology USD Million (2021-2026)
  • Table 188. China Healthcare Natural Language Processing, by End-User USD Million (2021-2026)
  • Table 189. Japan Healthcare Natural Language Processing, by Type USD Million (2021-2026)
  • Table 190. Japan Healthcare Natural Language Processing, by Application USD Million (2021-2026)
  • Table 191. Japan Healthcare Natural Language Processing, by Technology USD Million (2021-2026)
  • Table 192. Japan Healthcare Natural Language Processing, by End-User USD Million (2021-2026)
  • Table 193. India Healthcare Natural Language Processing, by Type USD Million (2021-2026)
  • Table 194. India Healthcare Natural Language Processing, by Application USD Million (2021-2026)
  • Table 195. India Healthcare Natural Language Processing, by Technology USD Million (2021-2026)
  • Table 196. India Healthcare Natural Language Processing, by End-User USD Million (2021-2026)
  • Table 197. South Korea Healthcare Natural Language Processing, by Type USD Million (2021-2026)
  • Table 198. South Korea Healthcare Natural Language Processing, by Application USD Million (2021-2026)
  • Table 199. South Korea Healthcare Natural Language Processing, by Technology USD Million (2021-2026)
  • Table 200. South Korea Healthcare Natural Language Processing, by End-User USD Million (2021-2026)
  • Table 201. Taiwan Healthcare Natural Language Processing, by Type USD Million (2021-2026)
  • Table 202. Taiwan Healthcare Natural Language Processing, by Application USD Million (2021-2026)
  • Table 203. Taiwan Healthcare Natural Language Processing, by Technology USD Million (2021-2026)
  • Table 204. Taiwan Healthcare Natural Language Processing, by End-User USD Million (2021-2026)
  • Table 205. Australia Healthcare Natural Language Processing, by Type USD Million (2021-2026)
  • Table 206. Australia Healthcare Natural Language Processing, by Application USD Million (2021-2026)
  • Table 207. Australia Healthcare Natural Language Processing, by Technology USD Million (2021-2026)
  • Table 208. Australia Healthcare Natural Language Processing, by End-User USD Million (2021-2026)
  • Table 209. Rest of Asia-Pacific Healthcare Natural Language Processing, by Type USD Million (2021-2026)
  • Table 210. Rest of Asia-Pacific Healthcare Natural Language Processing, by Application USD Million (2021-2026)
  • Table 211. Rest of Asia-Pacific Healthcare Natural Language Processing, by Technology USD Million (2021-2026)
  • Table 212. Rest of Asia-Pacific Healthcare Natural Language Processing, by End-User USD Million (2021-2026)
  • Table 213. Europe Healthcare Natural Language Processing, by Country USD Million (2021-2026)
  • Table 214. Europe Healthcare Natural Language Processing, by Type USD Million (2021-2026)
  • Table 215. Europe Healthcare Natural Language Processing, by Application USD Million (2021-2026)
  • Table 216. Europe Healthcare Natural Language Processing, by Technology USD Million (2021-2026)
  • Table 217. Europe Healthcare Natural Language Processing, by End-User USD Million (2021-2026)
  • Table 218. Germany Healthcare Natural Language Processing, by Type USD Million (2021-2026)
  • Table 219. Germany Healthcare Natural Language Processing, by Application USD Million (2021-2026)
  • Table 220. Germany Healthcare Natural Language Processing, by Technology USD Million (2021-2026)
  • Table 221. Germany Healthcare Natural Language Processing, by End-User USD Million (2021-2026)
  • Table 222. France Healthcare Natural Language Processing, by Type USD Million (2021-2026)
  • Table 223. France Healthcare Natural Language Processing, by Application USD Million (2021-2026)
  • Table 224. France Healthcare Natural Language Processing, by Technology USD Million (2021-2026)
  • Table 225. France Healthcare Natural Language Processing, by End-User USD Million (2021-2026)
  • Table 226. Italy Healthcare Natural Language Processing, by Type USD Million (2021-2026)
  • Table 227. Italy Healthcare Natural Language Processing, by Application USD Million (2021-2026)
  • Table 228. Italy Healthcare Natural Language Processing, by Technology USD Million (2021-2026)
  • Table 229. Italy Healthcare Natural Language Processing, by End-User USD Million (2021-2026)
  • Table 230. United Kingdom Healthcare Natural Language Processing, by Type USD Million (2021-2026)
  • Table 231. United Kingdom Healthcare Natural Language Processing, by Application USD Million (2021-2026)
  • Table 232. United Kingdom Healthcare Natural Language Processing, by Technology USD Million (2021-2026)
  • Table 233. United Kingdom Healthcare Natural Language Processing, by End-User USD Million (2021-2026)
  • Table 234. Netherlands Healthcare Natural Language Processing, by Type USD Million (2021-2026)
  • Table 235. Netherlands Healthcare Natural Language Processing, by Application USD Million (2021-2026)
  • Table 236. Netherlands Healthcare Natural Language Processing, by Technology USD Million (2021-2026)
  • Table 237. Netherlands Healthcare Natural Language Processing, by End-User USD Million (2021-2026)
  • Table 238. Rest of Europe Healthcare Natural Language Processing, by Type USD Million (2021-2026)
  • Table 239. Rest of Europe Healthcare Natural Language Processing, by Application USD Million (2021-2026)
  • Table 240. Rest of Europe Healthcare Natural Language Processing, by Technology USD Million (2021-2026)
  • Table 241. Rest of Europe Healthcare Natural Language Processing, by End-User USD Million (2021-2026)
  • Table 242. MEA Healthcare Natural Language Processing, by Country USD Million (2021-2026)
  • Table 243. MEA Healthcare Natural Language Processing, by Type USD Million (2021-2026)
  • Table 244. MEA Healthcare Natural Language Processing, by Application USD Million (2021-2026)
  • Table 245. MEA Healthcare Natural Language Processing, by Technology USD Million (2021-2026)
  • Table 246. MEA Healthcare Natural Language Processing, by End-User USD Million (2021-2026)
  • Table 247. Middle East Healthcare Natural Language Processing, by Type USD Million (2021-2026)
  • Table 248. Middle East Healthcare Natural Language Processing, by Application USD Million (2021-2026)
  • Table 249. Middle East Healthcare Natural Language Processing, by Technology USD Million (2021-2026)
  • Table 250. Middle East Healthcare Natural Language Processing, by End-User USD Million (2021-2026)
  • Table 251. Africa Healthcare Natural Language Processing, by Type USD Million (2021-2026)
  • Table 252. Africa Healthcare Natural Language Processing, by Application USD Million (2021-2026)
  • Table 253. Africa Healthcare Natural Language Processing, by Technology USD Million (2021-2026)
  • Table 254. Africa Healthcare Natural Language Processing, by End-User USD Million (2021-2026)
  • Table 255. North America Healthcare Natural Language Processing, by Country USD Million (2021-2026)
  • Table 256. North America Healthcare Natural Language Processing, by Type USD Million (2021-2026)
  • Table 257. North America Healthcare Natural Language Processing, by Application USD Million (2021-2026)
  • Table 258. North America Healthcare Natural Language Processing, by Technology USD Million (2021-2026)
  • Table 259. North America Healthcare Natural Language Processing, by End-User USD Million (2021-2026)
  • Table 260. United States Healthcare Natural Language Processing, by Type USD Million (2021-2026)
  • Table 261. United States Healthcare Natural Language Processing, by Application USD Million (2021-2026)
  • Table 262. United States Healthcare Natural Language Processing, by Technology USD Million (2021-2026)
  • Table 263. United States Healthcare Natural Language Processing, by End-User USD Million (2021-2026)
  • Table 264. Canada Healthcare Natural Language Processing, by Type USD Million (2021-2026)
  • Table 265. Canada Healthcare Natural Language Processing, by Application USD Million (2021-2026)
  • Table 266. Canada Healthcare Natural Language Processing, by Technology USD Million (2021-2026)
  • Table 267. Canada Healthcare Natural Language Processing, by End-User USD Million (2021-2026)
  • Table 268. Mexico Healthcare Natural Language Processing, by Type USD Million (2021-2026)
  • Table 269. Mexico Healthcare Natural Language Processing, by Application USD Million (2021-2026)
  • Table 270. Mexico Healthcare Natural Language Processing, by Technology USD Million (2021-2026)
  • Table 271. Mexico Healthcare Natural Language Processing, by End-User USD Million (2021-2026)
  • Table 272. Healthcare Natural Language Processing: by Type(USD/Units)
  • Table 273. Research Programs/Design for This Report
  • Table 274. Key Data Information from Secondary Sources
  • Table 275. Key Data Information from Primary Sources
List of Figures
  • Figure 1. Porters Five Forces
  • Figure 2. Supply/Value Chain
  • Figure 3. PESTEL analysis
  • Figure 4. Global Healthcare Natural Language Processing: by Type USD Million (2015-2020)
  • Figure 5. Global Healthcare Natural Language Processing: by Application USD Million (2015-2020)
  • Figure 6. Global Healthcare Natural Language Processing: by Technology USD Million (2015-2020)
  • Figure 7. Global Healthcare Natural Language Processing: by End-User USD Million (2015-2020)
  • Figure 8. South America Healthcare Natural Language Processing Share (%), by Country
  • Figure 9. Asia Pacific Healthcare Natural Language Processing Share (%), by Country
  • Figure 10. Europe Healthcare Natural Language Processing Share (%), by Country
  • Figure 11. MEA Healthcare Natural Language Processing Share (%), by Country
  • Figure 12. North America Healthcare Natural Language Processing Share (%), by Country
  • Figure 13. Global Healthcare Natural Language Processing: by Type USD/Units (2015-2020)
  • Figure 14. Global Healthcare Natural Language Processing share by Players 2020 (%)
  • Figure 15. Global Healthcare Natural Language Processing share by Players (Top 3) 2020(%)
  • Figure 16. Global Healthcare Natural Language Processing share by Players (Top 5) 2020(%)
  • Figure 17. BCG Matrix for key Companies
  • Figure 18. 3M (United States) Revenue, Net Income and Gross profit
  • Figure 19. 3M (United States) Revenue: by Geography 2020
  • Figure 20. Cerner (United States) Revenue, Net Income and Gross profit
  • Figure 21. Cerner (United States) Revenue: by Geography 2020
  • Figure 22. Nuance (United States) Revenue, Net Income and Gross profit
  • Figure 23. Nuance (United States) Revenue: by Geography 2020
  • Figure 24. Health Fidelity (United States) Revenue, Net Income and Gross profit
  • Figure 25. Health Fidelity (United States) Revenue: by Geography 2020
  • Figure 26. Dolbey (United States) Revenue, Net Income and Gross profit
  • Figure 27. Dolbey (United States) Revenue: by Geography 2020
  • Figure 28. Microsoft (United States) Revenue, Net Income and Gross profit
  • Figure 29. Microsoft (United States) Revenue: by Geography 2020
  • Figure 30. IBM (United States) Revenue, Net Income and Gross profit
  • Figure 31. IBM (United States) Revenue: by Geography 2020
  • Figure 32. Google (United States) Revenue, Net Income and Gross profit
  • Figure 33. Google (United States) Revenue: by Geography 2020
  • Figure 34. AWS (United States) Revenue, Net Income and Gross profit
  • Figure 35. AWS (United States) Revenue: by Geography 2020
  • Figure 36. Apixio (United States) Revenue, Net Income and Gross profit
  • Figure 37. Apixio (United States) Revenue: by Geography 2020
  • Figure 38. Averbis (Germany) Revenue, Net Income and Gross profit
  • Figure 39. Averbis (Germany) Revenue: by Geography 2020
  • Figure 40. Linguamatics (United Kingdom) Revenue, Net Income and Gross profit
  • Figure 41. Linguamatics (United Kingdom) Revenue: by Geography 2020
  • Figure 42. Global Healthcare Natural Language Processing: by Type USD Million (2021-2026)
  • Figure 43. Global Healthcare Natural Language Processing: by Application USD Million (2021-2026)
  • Figure 44. Global Healthcare Natural Language Processing: by Technology USD Million (2021-2026)
  • Figure 45. Global Healthcare Natural Language Processing: by End-User USD Million (2021-2026)
  • Figure 46. South America Healthcare Natural Language Processing Share (%), by Country
  • Figure 47. Asia Pacific Healthcare Natural Language Processing Share (%), by Country
  • Figure 48. Europe Healthcare Natural Language Processing Share (%), by Country
  • Figure 49. MEA Healthcare Natural Language Processing Share (%), by Country
  • Figure 50. North America Healthcare Natural Language Processing Share (%), by Country
  • Figure 51. Global Healthcare Natural Language Processing: by Type USD/Units (2021-2026)
Some of the key companies/manufacturers profiled in the report
  • 3M (United States)
  • Cerner (United States)
  • Nuance (United States)
  • Health Fidelity (United States)
  • Dolbey (United States)
  • Microsoft (United States)
  • IBM (United States)
  • Google (United States)
  • AWS (United States)
  • Apixio (United States)
  • Averbis (Germany)
  • Linguamatics (United Kingdom)
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