Global Machine Learning in Healthcare- Market

Machine Learning in Healthcare- Comprehensive Study by Type (Software Solutions, Hardware, Services), Application (Robot-Assisted Surgery, Virtual Assistants, Administrative Workflow Assistants, Connected Machines, Diagnosis, Clinical Trials, Fraud Detection, Cybersecurity, Dosage Error Reduction), End User (Hospitals & Clinics, Research Institutes, Animal Care Centres, Others) Players and Region - Global Market Outlook to 2027

Machine Learning in Healthcare- Market by XX Submarkets | Forecast Years 2022-2027  

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  • Summary
  • Market Segments
  • Table of Content
  • List of Table & Figures
  • Players Profiled
Machine Learning in Healthcare- Market Scope
Machine learning is a rapidly rising technology with exciting implications for healthcare. For instance, by crunching large volumes of data, machine learning technology can help healthcare professionals generate precise medicine solutions customized to individual characteristics. Machine learning is to conceptualize it as developing algorithms and apps based on past experiences and current data-both historical and real-time data. Rising Prevalence of Chronic Diseases have contributed to the need for Faster and Accurate Disease Detection. Increasing Technology Improvement of doctors during telemedicine sessions, as well as capture information during virtual visits to streamline workflows.

AttributesDetails
Study Period2017-2027
Base Year2021
UnitValue (USD Million)
Key Companies ProfiledNuance Communications, Inc. (United States), IBM Corporation (United States), Microsoft (United States), NVIDIA Corporation (United States), Intel Corporation (United States), DeepMind Technologies Limited (United Kingdom), Tempus (United States), PathAI (United States), Kareo (United States) and Beta Bionics (United States)
CAGR%


The companies of AI Platform for Digital Health that helps healthcare organizations accelerate their journey from business intelligence (BI) to AI to return on investment (ROI). The key manufacturers are targeting the innovations of the better technical characteristics. The key players are probable to keep a stronghold on the market over the anticipated period. The key players are accepting strategic decisions and are thinking upon mergers and acquisitions in order to maintain their presence in the market Research Analyst at AMA estimates that United States Players will contribute to the maximum growth of Global Machine Learning in Healthcare- market throughout the predicted period.

Nuance Communications, Inc. (United States), IBM Corporation (United States), Microsoft (United States), NVIDIA Corporation (United States), Intel Corporation (United States), DeepMind Technologies Limited (United Kingdom), Tempus (United States), PathAI (United States), Kareo (United States) and Beta Bionics (United States) are some of the key players that are part of study coverage. Additionally, the Players which are also part of the research are KenSci (United States), Ciox Health (United States), Subtle Medical (United States), Pfizer (United States) and Insitro (United States).

About Approach
The research aims to propose a patent-based approach in searching for potential technology partners as a supporting tool for enabling open innovation. The study also proposes a systematic searching process of technology partners as a preliminary step to select the emerging and key players that are involved in implementing market estimations. While patent analysis is employed to overcome the aforementioned data- and process-related limitations, as expenses occurred in that technology allows us to estimate the market size by evolving segments as target market from the total available market.

Segmentation Overview
The study have segmented the market of Global Machine Learning in Healthcare- market by Type , by Application (Robot-Assisted Surgery, Virtual Assistants, Administrative Workflow Assistants, Connected Machines, Diagnosis, Clinical Trials, Fraud Detection, Cybersecurity and Dosage Error Reduction) and Region with country level break-up.

On the basis of geography, the market of Machine Learning in Healthcare- has been segmented into South America (Brazil, Argentina, Rest of South America), Asia Pacific (China, Japan, India, South Korea, 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). region held largest market share in the year 2021.

Market Leaders and their expansionary development strategies
On 24th June 2021, Tegria announced the acquisition of KenSci, a leader in artificial intelligence platforms and applications for healthcare, with roots in Microsoft's Azure4Research program and the University of Washington. KenSci has been helping customers get more from their data for years, and they understand the vital roles invention and collaboration play in helping accelerate transformation across all facets of care.
On 29th Sep 2020, KenSci, a healthcare analytics and artificial intelligence (AI) company announced the launch of their AI Platform for Digital Health that helps healthcare organizations accelerate their journey from business intelligence (BI) to AI to return on investment (ROI). The re-imagined AI platform extends KenSci's runtime engine with BI-AI development capabilities and the latest predictive analytics technology that enables health organizations to develop BI and AI-based workloads in an easy and agile way.


Machine Learning in Healthcare- Market Dynamics:
AttributesDetails
Trends Influencing Market
  • Adoption of Technologies Based on Artificial Intelligence (AI) in Healthcare
  • Increasing Innovation in the robot-assisted surgeries and Development of Machine Learning
Key Restraints
  • Technical Limitations and Lack of Accuracy to Impede the Market Growth
Challenges
  • Challenge in Innovation of the Robot-assisted Surgeries and Development of Machine Learning
Market Opportunities
  • Increasing Technology Improvement of doctors during telemedicine sessions, as well as capture information during virtual visits to streamline workflows.
  • Growing Demand for technologies in healthcare industry are Growing Opportunities for Players
  • Government initiatives are Growing Number of Investments from Private Investors and Venture Capitalists


Key Target Audience
Machine Learning in Healthcare Manufacturers, Research and Development Institutes, Potential Investors, Hospitals, Regulatory Bodies and Others

Report Objectives / Segmentation Covered

By Type
  • Software Solutions
  • Hardware
  • Services
By Application
  • Robot-Assisted Surgery
  • Virtual Assistants
  • Administrative Workflow Assistants
  • Connected Machines
  • Diagnosis
  • Clinical Trials
  • Fraud Detection
  • Cybersecurity
  • Dosage Error Reduction
By End User
  • Hospitals & Clinics
  • Research Institutes
  • Animal Care Centres
  • Others

By Regions
  • South America
    • Brazil
    • Argentina
    • Rest of South America
  • Asia Pacific
    • China
    • Japan
    • India
    • South Korea
    • 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. Intelligence and Machine Learning are Largely Seen as Key Technologies that the Healthcare Industry
      • 3.2.2. Growing Demand for Datasets of Patient Health-related Digital Information is Driving the Growth
      • 3.2.3. Rising Prevalence of Chronic Diseases have Contributed to the need for Faster and Accurate Disease Detection
    • 3.3. Market Challenges
      • 3.3.1. Challenge in Innovation of the Robot-assisted Surgeries and Development of Machine Learning
    • 3.4. Market Trends
      • 3.4.1. Adoption of Technologies Based on Artificial Intelligence (AI) in Healthcare
      • 3.4.2. Increasing Innovation in the robot-assisted surgeries and Development of Machine Learning
  • 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 Machine Learning in Healthcare-, by Type, Application, End User and Region (value and price ) (2016-2021)
    • 5.1. Introduction
    • 5.2. Global Machine Learning in Healthcare- (Value)
      • 5.2.1. Global Machine Learning in Healthcare- by: Type (Value)
        • 5.2.1.1. Software Solutions
        • 5.2.1.2. Hardware
        • 5.2.1.3. Services
      • 5.2.2. Global Machine Learning in Healthcare- by: Application (Value)
        • 5.2.2.1. Robot-Assisted Surgery
        • 5.2.2.2. Virtual Assistants
        • 5.2.2.3. Administrative Workflow Assistants
        • 5.2.2.4. Connected Machines
        • 5.2.2.5. Diagnosis
        • 5.2.2.6. Clinical Trials
        • 5.2.2.7. Fraud Detection
        • 5.2.2.8. Cybersecurity
        • 5.2.2.9. Dosage Error Reduction
      • 5.2.3. Global Machine Learning in Healthcare- by: End User (Value)
        • 5.2.3.1. Hospitals & Clinics
        • 5.2.3.2. Research Institutes
        • 5.2.3.3. Animal Care Centres
        • 5.2.3.4. Others
      • 5.2.4. Global Machine Learning in Healthcare- Region
        • 5.2.4.1. South America
          • 5.2.4.1.1. Brazil
          • 5.2.4.1.2. Argentina
          • 5.2.4.1.3. Rest of South America
        • 5.2.4.2. Asia Pacific
          • 5.2.4.2.1. China
          • 5.2.4.2.2. Japan
          • 5.2.4.2.3. India
          • 5.2.4.2.4. South Korea
          • 5.2.4.2.5. Australia
          • 5.2.4.2.6. Rest of Asia-Pacific
        • 5.2.4.3. Europe
          • 5.2.4.3.1. Germany
          • 5.2.4.3.2. France
          • 5.2.4.3.3. Italy
          • 5.2.4.3.4. United Kingdom
          • 5.2.4.3.5. Netherlands
          • 5.2.4.3.6. Rest of Europe
        • 5.2.4.4. MEA
          • 5.2.4.4.1. Middle East
          • 5.2.4.4.2. Africa
        • 5.2.4.5. North America
          • 5.2.4.5.1. United States
          • 5.2.4.5.2. Canada
          • 5.2.4.5.3. Mexico
    • 5.3. Global Machine Learning in Healthcare- (Price)
      • 5.3.1. Global Machine Learning in Healthcare- by: Type (Price)
  • 6. Machine Learning in Healthcare-: 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 (2021)
    • 6.3. BCG Matrix
    • 6.4. Company Profile
      • 6.4.1. Nuance Communications, Inc. (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. IBM Corporation (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. Microsoft (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. NVIDIA Corporation (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. Intel Corporation (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. DeepMind Technologies Limited (United Kingdom)
        • 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. Tempus (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. PathAI (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. Kareo (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. Beta Bionics (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
  • 7. Global Machine Learning in Healthcare- Sale, by Type, Application, End User and Region (value and price ) (2022-2027)
    • 7.1. Introduction
    • 7.2. Global Machine Learning in Healthcare- (Value)
      • 7.2.1. Global Machine Learning in Healthcare- by: Type (Value)
        • 7.2.1.1. Software Solutions
        • 7.2.1.2. Hardware
        • 7.2.1.3. Services
      • 7.2.2. Global Machine Learning in Healthcare- by: Application (Value)
        • 7.2.2.1. Robot-Assisted Surgery
        • 7.2.2.2. Virtual Assistants
        • 7.2.2.3. Administrative Workflow Assistants
        • 7.2.2.4. Connected Machines
        • 7.2.2.5. Diagnosis
        • 7.2.2.6. Clinical Trials
        • 7.2.2.7. Fraud Detection
        • 7.2.2.8. Cybersecurity
        • 7.2.2.9. Dosage Error Reduction
      • 7.2.3. Global Machine Learning in Healthcare- by: End User (Value)
        • 7.2.3.1. Hospitals & Clinics
        • 7.2.3.2. Research Institutes
        • 7.2.3.3. Animal Care Centres
        • 7.2.3.4. Others
      • 7.2.4. Global Machine Learning in Healthcare- Region
        • 7.2.4.1. South America
          • 7.2.4.1.1. Brazil
          • 7.2.4.1.2. Argentina
          • 7.2.4.1.3. Rest of South America
        • 7.2.4.2. Asia Pacific
          • 7.2.4.2.1. China
          • 7.2.4.2.2. Japan
          • 7.2.4.2.3. India
          • 7.2.4.2.4. South Korea
          • 7.2.4.2.5. Australia
          • 7.2.4.2.6. Rest of Asia-Pacific
        • 7.2.4.3. Europe
          • 7.2.4.3.1. Germany
          • 7.2.4.3.2. France
          • 7.2.4.3.3. Italy
          • 7.2.4.3.4. United Kingdom
          • 7.2.4.3.5. Netherlands
          • 7.2.4.3.6. Rest of Europe
        • 7.2.4.4. MEA
          • 7.2.4.4.1. Middle East
          • 7.2.4.4.2. Africa
        • 7.2.4.5. North America
          • 7.2.4.5.1. United States
          • 7.2.4.5.2. Canada
          • 7.2.4.5.3. Mexico
    • 7.3. Global Machine Learning in Healthcare- (Price)
      • 7.3.1. Global Machine Learning in Healthcare- 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. Machine Learning in Healthcare-: by Type(USD Million)
  • Table 2. Machine Learning in Healthcare- Software Solutions , by Region USD Million (2016-2021)
  • Table 3. Machine Learning in Healthcare- Hardware , by Region USD Million (2016-2021)
  • Table 4. Machine Learning in Healthcare- Services , by Region USD Million (2016-2021)
  • Table 5. Machine Learning in Healthcare-: by Application(USD Million)
  • Table 6. Machine Learning in Healthcare- Robot-Assisted Surgery , by Region USD Million (2016-2021)
  • Table 7. Machine Learning in Healthcare- Virtual Assistants , by Region USD Million (2016-2021)
  • Table 8. Machine Learning in Healthcare- Administrative Workflow Assistants , by Region USD Million (2016-2021)
  • Table 9. Machine Learning in Healthcare- Connected Machines , by Region USD Million (2016-2021)
  • Table 10. Machine Learning in Healthcare- Diagnosis , by Region USD Million (2016-2021)
  • Table 11. Machine Learning in Healthcare- Clinical Trials , by Region USD Million (2016-2021)
  • Table 12. Machine Learning in Healthcare- Fraud Detection , by Region USD Million (2016-2021)
  • Table 13. Machine Learning in Healthcare- Cybersecurity , by Region USD Million (2016-2021)
  • Table 14. Machine Learning in Healthcare- Dosage Error Reduction , by Region USD Million (2016-2021)
  • Table 15. Machine Learning in Healthcare-: by End User(USD Million)
  • Table 16. Machine Learning in Healthcare- Hospitals & Clinics , by Region USD Million (2016-2021)
  • Table 17. Machine Learning in Healthcare- Research Institutes , by Region USD Million (2016-2021)
  • Table 18. Machine Learning in Healthcare- Animal Care Centres , by Region USD Million (2016-2021)
  • Table 19. Machine Learning in Healthcare- Others , by Region USD Million (2016-2021)
  • Table 20. South America Machine Learning in Healthcare-, by Country USD Million (2016-2021)
  • Table 21. South America Machine Learning in Healthcare-, by Type USD Million (2016-2021)
  • Table 22. South America Machine Learning in Healthcare-, by Application USD Million (2016-2021)
  • Table 23. South America Machine Learning in Healthcare-, by End User USD Million (2016-2021)
  • Table 24. Brazil Machine Learning in Healthcare-, by Type USD Million (2016-2021)
  • Table 25. Brazil Machine Learning in Healthcare-, by Application USD Million (2016-2021)
  • Table 26. Brazil Machine Learning in Healthcare-, by End User USD Million (2016-2021)
  • Table 27. Argentina Machine Learning in Healthcare-, by Type USD Million (2016-2021)
  • Table 28. Argentina Machine Learning in Healthcare-, by Application USD Million (2016-2021)
  • Table 29. Argentina Machine Learning in Healthcare-, by End User USD Million (2016-2021)
  • Table 30. Rest of South America Machine Learning in Healthcare-, by Type USD Million (2016-2021)
  • Table 31. Rest of South America Machine Learning in Healthcare-, by Application USD Million (2016-2021)
  • Table 32. Rest of South America Machine Learning in Healthcare-, by End User USD Million (2016-2021)
  • Table 33. Asia Pacific Machine Learning in Healthcare-, by Country USD Million (2016-2021)
  • Table 34. Asia Pacific Machine Learning in Healthcare-, by Type USD Million (2016-2021)
  • Table 35. Asia Pacific Machine Learning in Healthcare-, by Application USD Million (2016-2021)
  • Table 36. Asia Pacific Machine Learning in Healthcare-, by End User USD Million (2016-2021)
  • Table 37. China Machine Learning in Healthcare-, by Type USD Million (2016-2021)
  • Table 38. China Machine Learning in Healthcare-, by Application USD Million (2016-2021)
  • Table 39. China Machine Learning in Healthcare-, by End User USD Million (2016-2021)
  • Table 40. Japan Machine Learning in Healthcare-, by Type USD Million (2016-2021)
  • Table 41. Japan Machine Learning in Healthcare-, by Application USD Million (2016-2021)
  • Table 42. Japan Machine Learning in Healthcare-, by End User USD Million (2016-2021)
  • Table 43. India Machine Learning in Healthcare-, by Type USD Million (2016-2021)
  • Table 44. India Machine Learning in Healthcare-, by Application USD Million (2016-2021)
  • Table 45. India Machine Learning in Healthcare-, by End User USD Million (2016-2021)
  • Table 46. South Korea Machine Learning in Healthcare-, by Type USD Million (2016-2021)
  • Table 47. South Korea Machine Learning in Healthcare-, by Application USD Million (2016-2021)
  • Table 48. South Korea Machine Learning in Healthcare-, by End User USD Million (2016-2021)
  • Table 49. Australia Machine Learning in Healthcare-, by Type USD Million (2016-2021)
  • Table 50. Australia Machine Learning in Healthcare-, by Application USD Million (2016-2021)
  • Table 51. Australia Machine Learning in Healthcare-, by End User USD Million (2016-2021)
  • Table 52. Rest of Asia-Pacific Machine Learning in Healthcare-, by Type USD Million (2016-2021)
  • Table 53. Rest of Asia-Pacific Machine Learning in Healthcare-, by Application USD Million (2016-2021)
  • Table 54. Rest of Asia-Pacific Machine Learning in Healthcare-, by End User USD Million (2016-2021)
  • Table 55. Europe Machine Learning in Healthcare-, by Country USD Million (2016-2021)
  • Table 56. Europe Machine Learning in Healthcare-, by Type USD Million (2016-2021)
  • Table 57. Europe Machine Learning in Healthcare-, by Application USD Million (2016-2021)
  • Table 58. Europe Machine Learning in Healthcare-, by End User USD Million (2016-2021)
  • Table 59. Germany Machine Learning in Healthcare-, by Type USD Million (2016-2021)
  • Table 60. Germany Machine Learning in Healthcare-, by Application USD Million (2016-2021)
  • Table 61. Germany Machine Learning in Healthcare-, by End User USD Million (2016-2021)
  • Table 62. France Machine Learning in Healthcare-, by Type USD Million (2016-2021)
  • Table 63. France Machine Learning in Healthcare-, by Application USD Million (2016-2021)
  • Table 64. France Machine Learning in Healthcare-, by End User USD Million (2016-2021)
  • Table 65. Italy Machine Learning in Healthcare-, by Type USD Million (2016-2021)
  • Table 66. Italy Machine Learning in Healthcare-, by Application USD Million (2016-2021)
  • Table 67. Italy Machine Learning in Healthcare-, by End User USD Million (2016-2021)
  • Table 68. United Kingdom Machine Learning in Healthcare-, by Type USD Million (2016-2021)
  • Table 69. United Kingdom Machine Learning in Healthcare-, by Application USD Million (2016-2021)
  • Table 70. United Kingdom Machine Learning in Healthcare-, by End User USD Million (2016-2021)
  • Table 71. Netherlands Machine Learning in Healthcare-, by Type USD Million (2016-2021)
  • Table 72. Netherlands Machine Learning in Healthcare-, by Application USD Million (2016-2021)
  • Table 73. Netherlands Machine Learning in Healthcare-, by End User USD Million (2016-2021)
  • Table 74. Rest of Europe Machine Learning in Healthcare-, by Type USD Million (2016-2021)
  • Table 75. Rest of Europe Machine Learning in Healthcare-, by Application USD Million (2016-2021)
  • Table 76. Rest of Europe Machine Learning in Healthcare-, by End User USD Million (2016-2021)
  • Table 77. MEA Machine Learning in Healthcare-, by Country USD Million (2016-2021)
  • Table 78. MEA Machine Learning in Healthcare-, by Type USD Million (2016-2021)
  • Table 79. MEA Machine Learning in Healthcare-, by Application USD Million (2016-2021)
  • Table 80. MEA Machine Learning in Healthcare-, by End User USD Million (2016-2021)
  • Table 81. Middle East Machine Learning in Healthcare-, by Type USD Million (2016-2021)
  • Table 82. Middle East Machine Learning in Healthcare-, by Application USD Million (2016-2021)
  • Table 83. Middle East Machine Learning in Healthcare-, by End User USD Million (2016-2021)
  • Table 84. Africa Machine Learning in Healthcare-, by Type USD Million (2016-2021)
  • Table 85. Africa Machine Learning in Healthcare-, by Application USD Million (2016-2021)
  • Table 86. Africa Machine Learning in Healthcare-, by End User USD Million (2016-2021)
  • Table 87. North America Machine Learning in Healthcare-, by Country USD Million (2016-2021)
  • Table 88. North America Machine Learning in Healthcare-, by Type USD Million (2016-2021)
  • Table 89. North America Machine Learning in Healthcare-, by Application USD Million (2016-2021)
  • Table 90. North America Machine Learning in Healthcare-, by End User USD Million (2016-2021)
  • Table 91. United States Machine Learning in Healthcare-, by Type USD Million (2016-2021)
  • Table 92. United States Machine Learning in Healthcare-, by Application USD Million (2016-2021)
  • Table 93. United States Machine Learning in Healthcare-, by End User USD Million (2016-2021)
  • Table 94. Canada Machine Learning in Healthcare-, by Type USD Million (2016-2021)
  • Table 95. Canada Machine Learning in Healthcare-, by Application USD Million (2016-2021)
  • Table 96. Canada Machine Learning in Healthcare-, by End User USD Million (2016-2021)
  • Table 97. Mexico Machine Learning in Healthcare-, by Type USD Million (2016-2021)
  • Table 98. Mexico Machine Learning in Healthcare-, by Application USD Million (2016-2021)
  • Table 99. Mexico Machine Learning in Healthcare-, by End User USD Million (2016-2021)
  • Table 100. Machine Learning in Healthcare-: by Type(USD/Units)
  • Table 101. Company Basic Information, Sales Area and Its Competitors
  • Table 102. Company Basic Information, Sales Area and Its Competitors
  • Table 103. Company Basic Information, Sales Area and Its Competitors
  • Table 104. Company Basic Information, Sales Area and Its Competitors
  • Table 105. Company Basic Information, Sales Area and Its Competitors
  • Table 106. Company Basic Information, Sales Area and Its Competitors
  • Table 107. Company Basic Information, Sales Area and Its Competitors
  • Table 108. Company Basic Information, Sales Area and Its Competitors
  • Table 109. Company Basic Information, Sales Area and Its Competitors
  • Table 110. Company Basic Information, Sales Area and Its Competitors
  • Table 111. Machine Learning in Healthcare-: by Type(USD Million)
  • Table 112. Machine Learning in Healthcare- Software Solutions , by Region USD Million (2022-2027)
  • Table 113. Machine Learning in Healthcare- Hardware , by Region USD Million (2022-2027)
  • Table 114. Machine Learning in Healthcare- Services , by Region USD Million (2022-2027)
  • Table 115. Machine Learning in Healthcare-: by Application(USD Million)
  • Table 116. Machine Learning in Healthcare- Robot-Assisted Surgery , by Region USD Million (2022-2027)
  • Table 117. Machine Learning in Healthcare- Virtual Assistants , by Region USD Million (2022-2027)
  • Table 118. Machine Learning in Healthcare- Administrative Workflow Assistants , by Region USD Million (2022-2027)
  • Table 119. Machine Learning in Healthcare- Connected Machines , by Region USD Million (2022-2027)
  • Table 120. Machine Learning in Healthcare- Diagnosis , by Region USD Million (2022-2027)
  • Table 121. Machine Learning in Healthcare- Clinical Trials , by Region USD Million (2022-2027)
  • Table 122. Machine Learning in Healthcare- Fraud Detection , by Region USD Million (2022-2027)
  • Table 123. Machine Learning in Healthcare- Cybersecurity , by Region USD Million (2022-2027)
  • Table 124. Machine Learning in Healthcare- Dosage Error Reduction , by Region USD Million (2022-2027)
  • Table 125. Machine Learning in Healthcare-: by End User(USD Million)
  • Table 126. Machine Learning in Healthcare- Hospitals & Clinics , by Region USD Million (2022-2027)
  • Table 127. Machine Learning in Healthcare- Research Institutes , by Region USD Million (2022-2027)
  • Table 128. Machine Learning in Healthcare- Animal Care Centres , by Region USD Million (2022-2027)
  • Table 129. Machine Learning in Healthcare- Others , by Region USD Million (2022-2027)
  • Table 130. South America Machine Learning in Healthcare-, by Country USD Million (2022-2027)
  • Table 131. South America Machine Learning in Healthcare-, by Type USD Million (2022-2027)
  • Table 132. South America Machine Learning in Healthcare-, by Application USD Million (2022-2027)
  • Table 133. South America Machine Learning in Healthcare-, by End User USD Million (2022-2027)
  • Table 134. Brazil Machine Learning in Healthcare-, by Type USD Million (2022-2027)
  • Table 135. Brazil Machine Learning in Healthcare-, by Application USD Million (2022-2027)
  • Table 136. Brazil Machine Learning in Healthcare-, by End User USD Million (2022-2027)
  • Table 137. Argentina Machine Learning in Healthcare-, by Type USD Million (2022-2027)
  • Table 138. Argentina Machine Learning in Healthcare-, by Application USD Million (2022-2027)
  • Table 139. Argentina Machine Learning in Healthcare-, by End User USD Million (2022-2027)
  • Table 140. Rest of South America Machine Learning in Healthcare-, by Type USD Million (2022-2027)
  • Table 141. Rest of South America Machine Learning in Healthcare-, by Application USD Million (2022-2027)
  • Table 142. Rest of South America Machine Learning in Healthcare-, by End User USD Million (2022-2027)
  • Table 143. Asia Pacific Machine Learning in Healthcare-, by Country USD Million (2022-2027)
  • Table 144. Asia Pacific Machine Learning in Healthcare-, by Type USD Million (2022-2027)
  • Table 145. Asia Pacific Machine Learning in Healthcare-, by Application USD Million (2022-2027)
  • Table 146. Asia Pacific Machine Learning in Healthcare-, by End User USD Million (2022-2027)
  • Table 147. China Machine Learning in Healthcare-, by Type USD Million (2022-2027)
  • Table 148. China Machine Learning in Healthcare-, by Application USD Million (2022-2027)
  • Table 149. China Machine Learning in Healthcare-, by End User USD Million (2022-2027)
  • Table 150. Japan Machine Learning in Healthcare-, by Type USD Million (2022-2027)
  • Table 151. Japan Machine Learning in Healthcare-, by Application USD Million (2022-2027)
  • Table 152. Japan Machine Learning in Healthcare-, by End User USD Million (2022-2027)
  • Table 153. India Machine Learning in Healthcare-, by Type USD Million (2022-2027)
  • Table 154. India Machine Learning in Healthcare-, by Application USD Million (2022-2027)
  • Table 155. India Machine Learning in Healthcare-, by End User USD Million (2022-2027)
  • Table 156. South Korea Machine Learning in Healthcare-, by Type USD Million (2022-2027)
  • Table 157. South Korea Machine Learning in Healthcare-, by Application USD Million (2022-2027)
  • Table 158. South Korea Machine Learning in Healthcare-, by End User USD Million (2022-2027)
  • Table 159. Australia Machine Learning in Healthcare-, by Type USD Million (2022-2027)
  • Table 160. Australia Machine Learning in Healthcare-, by Application USD Million (2022-2027)
  • Table 161. Australia Machine Learning in Healthcare-, by End User USD Million (2022-2027)
  • Table 162. Rest of Asia-Pacific Machine Learning in Healthcare-, by Type USD Million (2022-2027)
  • Table 163. Rest of Asia-Pacific Machine Learning in Healthcare-, by Application USD Million (2022-2027)
  • Table 164. Rest of Asia-Pacific Machine Learning in Healthcare-, by End User USD Million (2022-2027)
  • Table 165. Europe Machine Learning in Healthcare-, by Country USD Million (2022-2027)
  • Table 166. Europe Machine Learning in Healthcare-, by Type USD Million (2022-2027)
  • Table 167. Europe Machine Learning in Healthcare-, by Application USD Million (2022-2027)
  • Table 168. Europe Machine Learning in Healthcare-, by End User USD Million (2022-2027)
  • Table 169. Germany Machine Learning in Healthcare-, by Type USD Million (2022-2027)
  • Table 170. Germany Machine Learning in Healthcare-, by Application USD Million (2022-2027)
  • Table 171. Germany Machine Learning in Healthcare-, by End User USD Million (2022-2027)
  • Table 172. France Machine Learning in Healthcare-, by Type USD Million (2022-2027)
  • Table 173. France Machine Learning in Healthcare-, by Application USD Million (2022-2027)
  • Table 174. France Machine Learning in Healthcare-, by End User USD Million (2022-2027)
  • Table 175. Italy Machine Learning in Healthcare-, by Type USD Million (2022-2027)
  • Table 176. Italy Machine Learning in Healthcare-, by Application USD Million (2022-2027)
  • Table 177. Italy Machine Learning in Healthcare-, by End User USD Million (2022-2027)
  • Table 178. United Kingdom Machine Learning in Healthcare-, by Type USD Million (2022-2027)
  • Table 179. United Kingdom Machine Learning in Healthcare-, by Application USD Million (2022-2027)
  • Table 180. United Kingdom Machine Learning in Healthcare-, by End User USD Million (2022-2027)
  • Table 181. Netherlands Machine Learning in Healthcare-, by Type USD Million (2022-2027)
  • Table 182. Netherlands Machine Learning in Healthcare-, by Application USD Million (2022-2027)
  • Table 183. Netherlands Machine Learning in Healthcare-, by End User USD Million (2022-2027)
  • Table 184. Rest of Europe Machine Learning in Healthcare-, by Type USD Million (2022-2027)
  • Table 185. Rest of Europe Machine Learning in Healthcare-, by Application USD Million (2022-2027)
  • Table 186. Rest of Europe Machine Learning in Healthcare-, by End User USD Million (2022-2027)
  • Table 187. MEA Machine Learning in Healthcare-, by Country USD Million (2022-2027)
  • Table 188. MEA Machine Learning in Healthcare-, by Type USD Million (2022-2027)
  • Table 189. MEA Machine Learning in Healthcare-, by Application USD Million (2022-2027)
  • Table 190. MEA Machine Learning in Healthcare-, by End User USD Million (2022-2027)
  • Table 191. Middle East Machine Learning in Healthcare-, by Type USD Million (2022-2027)
  • Table 192. Middle East Machine Learning in Healthcare-, by Application USD Million (2022-2027)
  • Table 193. Middle East Machine Learning in Healthcare-, by End User USD Million (2022-2027)
  • Table 194. Africa Machine Learning in Healthcare-, by Type USD Million (2022-2027)
  • Table 195. Africa Machine Learning in Healthcare-, by Application USD Million (2022-2027)
  • Table 196. Africa Machine Learning in Healthcare-, by End User USD Million (2022-2027)
  • Table 197. North America Machine Learning in Healthcare-, by Country USD Million (2022-2027)
  • Table 198. North America Machine Learning in Healthcare-, by Type USD Million (2022-2027)
  • Table 199. North America Machine Learning in Healthcare-, by Application USD Million (2022-2027)
  • Table 200. North America Machine Learning in Healthcare-, by End User USD Million (2022-2027)
  • Table 201. United States Machine Learning in Healthcare-, by Type USD Million (2022-2027)
  • Table 202. United States Machine Learning in Healthcare-, by Application USD Million (2022-2027)
  • Table 203. United States Machine Learning in Healthcare-, by End User USD Million (2022-2027)
  • Table 204. Canada Machine Learning in Healthcare-, by Type USD Million (2022-2027)
  • Table 205. Canada Machine Learning in Healthcare-, by Application USD Million (2022-2027)
  • Table 206. Canada Machine Learning in Healthcare-, by End User USD Million (2022-2027)
  • Table 207. Mexico Machine Learning in Healthcare-, by Type USD Million (2022-2027)
  • Table 208. Mexico Machine Learning in Healthcare-, by Application USD Million (2022-2027)
  • Table 209. Mexico Machine Learning in Healthcare-, by End User USD Million (2022-2027)
  • Table 210. Machine Learning in Healthcare-: by Type(USD/Units)
  • Table 211. Research Programs/Design for This Report
  • Table 212. Key Data Information from Secondary Sources
  • Table 213. 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 Machine Learning in Healthcare-: by Type USD Million (2016-2021)
  • Figure 5. Global Machine Learning in Healthcare-: by Application USD Million (2016-2021)
  • Figure 6. Global Machine Learning in Healthcare-: by End User USD Million (2016-2021)
  • Figure 7. South America Machine Learning in Healthcare- Share (%), by Country
  • Figure 8. Asia Pacific Machine Learning in Healthcare- Share (%), by Country
  • Figure 9. Europe Machine Learning in Healthcare- Share (%), by Country
  • Figure 10. MEA Machine Learning in Healthcare- Share (%), by Country
  • Figure 11. North America Machine Learning in Healthcare- Share (%), by Country
  • Figure 12. Global Machine Learning in Healthcare-: by Type USD/Units (2016-2021)
  • Figure 13. Global Machine Learning in Healthcare- share by Players 2021 (%)
  • Figure 14. Global Machine Learning in Healthcare- share by Players (Top 3) 2021(%)
  • Figure 15. Global Machine Learning in Healthcare- share by Players (Top 5) 2021(%)
  • Figure 16. BCG Matrix for key Companies
  • Figure 17. Nuance Communications, Inc. (United States) Revenue, Net Income and Gross profit
  • Figure 18. Nuance Communications, Inc. (United States) Revenue: by Geography 2021
  • Figure 19. IBM Corporation (United States) Revenue, Net Income and Gross profit
  • Figure 20. IBM Corporation (United States) Revenue: by Geography 2021
  • Figure 21. Microsoft (United States) Revenue, Net Income and Gross profit
  • Figure 22. Microsoft (United States) Revenue: by Geography 2021
  • Figure 23. NVIDIA Corporation (United States) Revenue, Net Income and Gross profit
  • Figure 24. NVIDIA Corporation (United States) Revenue: by Geography 2021
  • Figure 25. Intel Corporation (United States) Revenue, Net Income and Gross profit
  • Figure 26. Intel Corporation (United States) Revenue: by Geography 2021
  • Figure 27. DeepMind Technologies Limited (United Kingdom) Revenue, Net Income and Gross profit
  • Figure 28. DeepMind Technologies Limited (United Kingdom) Revenue: by Geography 2021
  • Figure 29. Tempus (United States) Revenue, Net Income and Gross profit
  • Figure 30. Tempus (United States) Revenue: by Geography 2021
  • Figure 31. PathAI (United States) Revenue, Net Income and Gross profit
  • Figure 32. PathAI (United States) Revenue: by Geography 2021
  • Figure 33. Kareo (United States) Revenue, Net Income and Gross profit
  • Figure 34. Kareo (United States) Revenue: by Geography 2021
  • Figure 35. Beta Bionics (United States) Revenue, Net Income and Gross profit
  • Figure 36. Beta Bionics (United States) Revenue: by Geography 2021
  • Figure 37. Global Machine Learning in Healthcare-: by Type USD Million (2022-2027)
  • Figure 38. Global Machine Learning in Healthcare-: by Application USD Million (2022-2027)
  • Figure 39. Global Machine Learning in Healthcare-: by End User USD Million (2022-2027)
  • Figure 40. South America Machine Learning in Healthcare- Share (%), by Country
  • Figure 41. Asia Pacific Machine Learning in Healthcare- Share (%), by Country
  • Figure 42. Europe Machine Learning in Healthcare- Share (%), by Country
  • Figure 43. MEA Machine Learning in Healthcare- Share (%), by Country
  • Figure 44. North America Machine Learning in Healthcare- Share (%), by Country
  • Figure 45. Global Machine Learning in Healthcare-: by Type USD/Units (2022-2027)
List of companies from research coverage that are profiled in the study
  • Nuance Communications, Inc. (United States)
  • IBM Corporation (United States)
  • Microsoft (United States)
  • NVIDIA Corporation (United States)
  • Intel Corporation (United States)
  • DeepMind Technologies Limited (United Kingdom)
  • Tempus (United States)
  • PathAI (United States)
  • Kareo (United States)
  • Beta Bionics (United States)
Additional players considered in the study are as follows:
KenSci (United States) , Ciox Health (United States) , Subtle Medical (United States) , Pfizer (United States) , Insitro (United States)
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Key Highlights of Report


Aug 2022 240 Pages 94 Tables Base Year: 2021 Coverage: 15+ Companies; 18 Countries

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Global Machine Learning in Healthcare- Market Quantitative research analysis
Global Machine Learning in Healthcare- Market Qualitative Industry Analysis
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Frequently Asked Questions (FAQ):

The key segments that are playing vital role in Machine Learning in Healthcare- Market are by type [Software Solutions, Hardware and Services], by end use application [Robot-Assisted Surgery, Virtual Assistants, Administrative Workflow Assistants, Connected Machines, Diagnosis, Clinical Trials, Fraud Detection, Cybersecurity and Dosage Error Reduction].
The Machine Learning in Healthcare- Market is gaining popularity and expected to see strong valuation by 2027.
  • Intelligence and Machine Learning are Largely Seen as Key Technologies that the Healthcare Industry
  • Growing Demand for Datasets of Patient Health-related Digital Information is Driving the Growth
  • Rising Prevalence of Chronic Diseases have Contributed to the need for Faster and Accurate Disease Detection

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