Global Deep Learning in Healthcare Market 2024 by Company, Regions, Type and Application, Forecast to 2030
Page: 111
Published Date: 08 Jan 2024
Category: Service & Software
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Description
Table of Contents
Table of Figures
Research Methodology
Companies Mentioned
Related Reports
Product Tags
Table of Contents
Table of Figures
Research Methodology
Companies Mentioned
Related Reports
Product Tags
Description
According to our (Global Info Research) latest study, the global Deep Learning in Healthcare market size was valued at USD million in 2023 and is forecast to a readjusted size of USD million by 2030 with a CAGR of % during review period.
Deep learning algorithms are capable of detecting more advanced threats and are not reliant on remembering known signatures and common attack patterns. Instead, they learn the system and can recognize suspicious activities that might indicate the presence of bad actors or malware
Deep Learning is a subfield of machine learning that focuses on training artificial neural networks to mimic human cognitive processes, such as visual, auditory, and linguistic understanding. It has seen significant growth and adoption across various industries, including search technology, data mining, machine translation, natural language processing, multimedia learning, speech recognition, and recommendation systems.
The Deep Learning market is expected to grow at a rapid pace in the coming years, driven by increasing demand for advanced analytics, growing adoption of AI in various industries, and improvements in computational capabilities.
Some trends driving the Deep Learning market include:
1. The increasing availability of large datasets: As the volume, variety, and complexity of data continue to grow, Deep Learning algorithms can leverage these datasets to improve their performance and accuracy.
2. Adoption in industries: Deep Learning is being widely adopted in industries such as healthcare, finance, retail, automotive, and cybersecurity to automate tasks, improve efficiency, and make data-driven decisions.
3. Enhanced automation and robotics: Deep Learning is enabling the development of advanced robots and autonomous systems that can perform tasks requiring human-like intelligence.
4. Integration with other AI technologies: Deep Learning is increasingly being combined with other AI technologies such as machine learning, computer vision, and natural language processing to create more sophisticated applications.
5. Progress in hardware and infrastructure: Advances in hardware and infrastructure, such as GPUs and cloud computing, have made it possible to deploy and scale Deep Learning models more efficiently and cost-effectively.
6. Ongoing research and development: The Deep Learning field is constantly evolving, with researchers and developers working on improving algorithms, models, and applications.
Overall, the Deep Learning market is expected to continue its strong growth trajectory in the coming years, as more and more industries adopt these advanced technologies to drive innovation and improve operations.
The Global Info Research report includes an overview of the development of the Deep Learning in Healthcare industry chain, the market status of Patient Data & Risk Analysis (Hardware, Software), Lifestyle Management & Monitoring (Hardware, Software), and key enterprises in developed and developing market, and analysed the cutting-edge technology, patent, hot applications and market trends of Deep Learning in Healthcare.
Regionally, the report analyzes the Deep Learning in Healthcare markets in key regions. North America and Europe are experiencing steady growth, driven by government initiatives and increasing consumer awareness. Asia-Pacific, particularly China, leads the global Deep Learning in Healthcare market, with robust domestic demand, supportive policies, and a strong manufacturing base.
Key Features:
The report presents comprehensive understanding of the Deep Learning in Healthcare market. It provides a holistic view of the industry, as well as detailed insights into individual components and stakeholders. The report analysis market dynamics, trends, challenges, and opportunities within the Deep Learning in Healthcare industry.
The report involves analyzing the market at a macro level:
Market Sizing and Segmentation: Report collect data on the overall market size, including the revenue generated, and market share of different by Type (e.g., Hardware, Software).
Industry Analysis: Report analyse the broader industry trends, such as government policies and regulations, technological advancements, consumer preferences, and market dynamics. This analysis helps in understanding the key drivers and challenges influencing the Deep Learning in Healthcare market.
Regional Analysis: The report involves examining the Deep Learning in Healthcare market at a regional or national level. Report analyses regional factors such as government incentives, infrastructure development, economic conditions, and consumer behaviour to identify variations and opportunities within different markets.
Market Projections: Report covers the gathered data and analysis to make future projections and forecasts for the Deep Learning in Healthcare market. This may include estimating market growth rates, predicting market demand, and identifying emerging trends.
The report also involves a more granular approach to Deep Learning in Healthcare:
Company Analysis: Report covers individual Deep Learning in Healthcare players, suppliers, and other relevant industry players. This analysis includes studying their financial performance, market positioning, product portfolios, partnerships, and strategies.
Consumer Analysis: Report covers data on consumer behaviour, preferences, and attitudes towards Deep Learning in Healthcare This may involve surveys, interviews, and analysis of consumer reviews and feedback from different by Application (Patient Data & Risk Analysis, Lifestyle Management & Monitoring).
Technology Analysis: Report covers specific technologies relevant to Deep Learning in Healthcare. It assesses the current state, advancements, and potential future developments in Deep Learning in Healthcare areas.
Competitive Landscape: By analyzing individual companies, suppliers, and consumers, the report present insights into the competitive landscape of the Deep Learning in Healthcare market. This analysis helps understand market share, competitive advantages, and potential areas for differentiation among industry players.
Market Validation: The report involves validating findings and projections through primary research, such as surveys, interviews, and focus groups.
Market Segmentation
Deep Learning in Healthcare market is split by Type and by Application. For the period 2019-2030, the growth among segments provides accurate calculations and forecasts for consumption value by Type, and by Application in terms of value.
Market segment by Type
Hardware
Software
Service
Market segment by Application
Patient Data & Risk Analysis
Lifestyle Management & Monitoring
Precision Medicine
Inpatient Care & Hospital Management
Medical Imaging & Diagnostics
Drug Discovery
Other
Market segment by players, this report covers
NVIDIA (US)
Intel (US)
Xilinx (US)
Samsung Electronics (South Korea)
Micron Technology (US)
Qualcomm (US)
IBM (US)
Google (US)
Microsoft (US)
AWS (US)
Graphcore (UK)
Mythic (US)
Adapteva (US)
Koniku (US)
Market segment by regions, regional analysis covers
North America (United States, Canada, and Mexico)
Europe (Germany, France, UK, Russia, Italy, and Rest of Europe)
Asia-Pacific (China, Japan, South Korea, India, Southeast Asia, Australia and Rest of Asia-Pacific)
South America (Brazil, Argentina and Rest of South America)
Middle East & Africa (Turkey, Saudi Arabia, UAE, Rest of Middle East & Africa)
The content of the study subjects, includes a total of 13 chapters:
Chapter 1, to describe Deep Learning in Healthcare product scope, market overview, market estimation caveats and base year.
Chapter 2, to profile the top players of Deep Learning in Healthcare, with revenue, gross margin and global market share of Deep Learning in Healthcare from 2019 to 2024.
Chapter 3, the Deep Learning in Healthcare competitive situation, revenue and global market share of top players are analyzed emphatically by landscape contrast.
Chapter 4 and 5, to segment the market size by Type and application, with consumption value and growth rate by Type, application, from 2019 to 2030.
Chapter 6, 7, 8, 9, and 10, to break the market size data at the country level, with revenue and market share for key countries in the world, from 2019 to 2024.and Deep Learning in Healthcare market forecast, by regions, type and application, with consumption value, from 2025 to 2030.
Chapter 11, market dynamics, drivers, restraints, trends and Porters Five Forces analysis.
Chapter 12, the key raw materials and key suppliers, and industry chain of Deep Learning in Healthcare.
Chapter 13, to describe Deep Learning in Healthcare research findings and conclusion.
Table of Contents
1 Market Overview
1.1 Product Overview and Scope of Deep Learning in Healthcare
1.2 Market Estimation Caveats and Base Year
1.3 Classification of Deep Learning in Healthcare by Type
1.3.1 Overview: Global Deep Learning in Healthcare Market Size by Type: 2019 Versus 2023 Versus 2030
1.3.2 Global Deep Learning in Healthcare Consumption Value Market Share by Type in 2023
1.3.3 Hardware
1.3.4 Software
1.3.5 Service
1.4 Global Deep Learning in Healthcare Market by Application
1.4.1 Overview: Global Deep Learning in Healthcare Market Size by Application: 2019 Versus 2023 Versus 2030
1.4.2 Patient Data & Risk Analysis
1.4.3 Lifestyle Management & Monitoring
1.4.4 Precision Medicine
1.4.5 Inpatient Care & Hospital Management
1.4.6 Medical Imaging & Diagnostics
1.4.7 Drug Discovery
1.4.8 Other
1.5 Global Deep Learning in Healthcare Market Size & Forecast
1.6 Global Deep Learning in Healthcare Market Size and Forecast by Region
1.6.1 Global Deep Learning in Healthcare Market Size by Region: 2019 VS 2023 VS 2030
1.6.2 Global Deep Learning in Healthcare Market Size by Region, (2019-2030)
1.6.3 North America Deep Learning in Healthcare Market Size and Prospect (2019-2030)
1.6.4 Europe Deep Learning in Healthcare Market Size and Prospect (2019-2030)
1.6.5 Asia-Pacific Deep Learning in Healthcare Market Size and Prospect (2019-2030)
1.6.6 South America Deep Learning in Healthcare Market Size and Prospect (2019-2030)
1.6.7 Middle East and Africa Deep Learning in Healthcare Market Size and Prospect (2019-2030)
2.1 NVIDIA (US)
2.1.1 NVIDIA (US) Details
2.1.2 NVIDIA (US) Major Business
2.1.3 NVIDIA (US) Deep Learning in Healthcare Product and Solutions
2.1.4 NVIDIA (US) Deep Learning in Healthcare Revenue, Gross Margin and Market Share (2019-2024)
2.1.5 NVIDIA (US) Recent Developments and Future Plans
2.2 Intel (US)
2.2.1 Intel (US) Details
2.2.2 Intel (US) Major Business
2.2.3 Intel (US) Deep Learning in Healthcare Product and Solutions
2.2.4 Intel (US) Deep Learning in Healthcare Revenue, Gross Margin and Market Share (2019-2024)
2.2.5 Intel (US) Recent Developments and Future Plans
2.3 Xilinx (US)
2.3.1 Xilinx (US) Details
2.3.2 Xilinx (US) Major Business
2.3.3 Xilinx (US) Deep Learning in Healthcare Product and Solutions
2.3.4 Xilinx (US) Deep Learning in Healthcare Revenue, Gross Margin and Market Share (2019-2024)
2.3.5 Xilinx (US) Recent Developments and Future Plans
2.4 Samsung Electronics (South Korea)
2.4.1 Samsung Electronics (South Korea) Details
2.4.2 Samsung Electronics (South Korea) Major Business
2.4.3 Samsung Electronics (South Korea) Deep Learning in Healthcare Product and Solutions
2.4.4 Samsung Electronics (South Korea) Deep Learning in Healthcare Revenue, Gross Margin and Market Share (2019-2024)
2.4.5 Samsung Electronics (South Korea) Recent Developments and Future Plans
2.5 Micron Technology (US)
2.5.1 Micron Technology (US) Details
2.5.2 Micron Technology (US) Major Business
2.5.3 Micron Technology (US) Deep Learning in Healthcare Product and Solutions
2.5.4 Micron Technology (US) Deep Learning in Healthcare Revenue, Gross Margin and Market Share (2019-2024)
2.5.5 Micron Technology (US) Recent Developments and Future Plans
2.6 Qualcomm (US)
2.6.1 Qualcomm (US) Details
2.6.2 Qualcomm (US) Major Business
2.6.3 Qualcomm (US) Deep Learning in Healthcare Product and Solutions
2.6.4 Qualcomm (US) Deep Learning in Healthcare Revenue, Gross Margin and Market Share (2019-2024)
2.6.5 Qualcomm (US) Recent Developments and Future Plans
2.7 IBM (US)
2.7.1 IBM (US) Details
2.7.2 IBM (US) Major Business
2.7.3 IBM (US) Deep Learning in Healthcare Product and Solutions
2.7.4 IBM (US) Deep Learning in Healthcare Revenue, Gross Margin and Market Share (2019-2024)
2.7.5 IBM (US) Recent Developments and Future Plans
2.8 Google (US)
2.8.1 Google (US) Details
2.8.2 Google (US) Major Business
2.8.3 Google (US) Deep Learning in Healthcare Product and Solutions
2.8.4 Google (US) Deep Learning in Healthcare Revenue, Gross Margin and Market Share (2019-2024)
2.8.5 Google (US) Recent Developments and Future Plans
2.9 Microsoft (US)
2.9.1 Microsoft (US) Details
2.9.2 Microsoft (US) Major Business
2.9.3 Microsoft (US) Deep Learning in Healthcare Product and Solutions
2.9.4 Microsoft (US) Deep Learning in Healthcare Revenue, Gross Margin and Market Share (2019-2024)
2.9.5 Microsoft (US) Recent Developments and Future Plans
2.10 AWS (US)
2.10.1 AWS (US) Details
2.10.2 AWS (US) Major Business
2.10.3 AWS (US) Deep Learning in Healthcare Product and Solutions
2.10.4 AWS (US) Deep Learning in Healthcare Revenue, Gross Margin and Market Share (2019-2024)
2.10.5 AWS (US) Recent Developments and Future Plans
2.11 Graphcore (UK)
2.11.1 Graphcore (UK) Details
2.11.2 Graphcore (UK) Major Business
2.11.3 Graphcore (UK) Deep Learning in Healthcare Product and Solutions
2.11.4 Graphcore (UK) Deep Learning in Healthcare Revenue, Gross Margin and Market Share (2019-2024)
2.11.5 Graphcore (UK) Recent Developments and Future Plans
2.12 Mythic (US)
2.12.1 Mythic (US) Details
2.12.2 Mythic (US) Major Business
2.12.3 Mythic (US) Deep Learning in Healthcare Product and Solutions
2.12.4 Mythic (US) Deep Learning in Healthcare Revenue, Gross Margin and Market Share (2019-2024)
2.12.5 Mythic (US) Recent Developments and Future Plans
2.13 Adapteva (US)
2.13.1 Adapteva (US) Details
2.13.2 Adapteva (US) Major Business
2.13.3 Adapteva (US) Deep Learning in Healthcare Product and Solutions
2.13.4 Adapteva (US) Deep Learning in Healthcare Revenue, Gross Margin and Market Share (2019-2024)
2.13.5 Adapteva (US) Recent Developments and Future Plans
2.14 Koniku (US)
2.14.1 Koniku (US) Details
2.14.2 Koniku (US) Major Business
2.14.3 Koniku (US) Deep Learning in Healthcare Product and Solutions
2.14.4 Koniku (US) Deep Learning in Healthcare Revenue, Gross Margin and Market Share (2019-2024)
2.14.5 Koniku (US) Recent Developments and Future Plans
3.1 Global Deep Learning in Healthcare Revenue and Share by Players (2019-2024)
3.2 Market Share Analysis (2023)
3.2.1 Market Share of Deep Learning in Healthcare by Company Revenue
3.2.2 Top 3 Deep Learning in Healthcare Players Market Share in 2023
3.2.3 Top 6 Deep Learning in Healthcare Players Market Share in 2023
3.3 Deep Learning in Healthcare Market: Overall Company Footprint Analysis
3.3.1 Deep Learning in Healthcare Market: Region Footprint
3.3.2 Deep Learning in Healthcare Market: Company Product Type Footprint
3.3.3 Deep Learning in Healthcare Market: Company Product Application Footprint
3.4 New Market Entrants and Barriers to Market Entry
3.5 Mergers, Acquisition, Agreements, and Collaborations
4.1 Global Deep Learning in Healthcare Consumption Value and Market Share by Type (2019-2024)
4.2 Global Deep Learning in Healthcare Market Forecast by Type (2025-2030)
5.1 Global Deep Learning in Healthcare Consumption Value Market Share by Application (2019-2024)
5.2 Global Deep Learning in Healthcare Market Forecast by Application (2025-2030)
6.1 North America Deep Learning in Healthcare Consumption Value by Type (2019-2030)
6.2 North America Deep Learning in Healthcare Consumption Value by Application (2019-2030)
6.3 North America Deep Learning in Healthcare Market Size by Country
6.3.1 North America Deep Learning in Healthcare Consumption Value by Country (2019-2030)
6.3.2 United States Deep Learning in Healthcare Market Size and Forecast (2019-2030)
6.3.3 Canada Deep Learning in Healthcare Market Size and Forecast (2019-2030)
6.3.4 Mexico Deep Learning in Healthcare Market Size and Forecast (2019-2030)
7.1 Europe Deep Learning in Healthcare Consumption Value by Type (2019-2030)
7.2 Europe Deep Learning in Healthcare Consumption Value by Application (2019-2030)
7.3 Europe Deep Learning in Healthcare Market Size by Country
7.3.1 Europe Deep Learning in Healthcare Consumption Value by Country (2019-2030)
7.3.2 Germany Deep Learning in Healthcare Market Size and Forecast (2019-2030)
7.3.3 France Deep Learning in Healthcare Market Size and Forecast (2019-2030)
7.3.4 United Kingdom Deep Learning in Healthcare Market Size and Forecast (2019-2030)
7.3.5 Russia Deep Learning in Healthcare Market Size and Forecast (2019-2030)
7.3.6 Italy Deep Learning in Healthcare Market Size and Forecast (2019-2030)
8.1 Asia-Pacific Deep Learning in Healthcare Consumption Value by Type (2019-2030)
8.2 Asia-Pacific Deep Learning in Healthcare Consumption Value by Application (2019-2030)
8.3 Asia-Pacific Deep Learning in Healthcare Market Size by Region
8.3.1 Asia-Pacific Deep Learning in Healthcare Consumption Value by Region (2019-2030)
8.3.2 China Deep Learning in Healthcare Market Size and Forecast (2019-2030)
8.3.3 Japan Deep Learning in Healthcare Market Size and Forecast (2019-2030)
8.3.4 South Korea Deep Learning in Healthcare Market Size and Forecast (2019-2030)
8.3.5 India Deep Learning in Healthcare Market Size and Forecast (2019-2030)
8.3.6 Southeast Asia Deep Learning in Healthcare Market Size and Forecast (2019-2030)
8.3.7 Australia Deep Learning in Healthcare Market Size and Forecast (2019-2030)
9.1 South America Deep Learning in Healthcare Consumption Value by Type (2019-2030)
9.2 South America Deep Learning in Healthcare Consumption Value by Application (2019-2030)
9.3 South America Deep Learning in Healthcare Market Size by Country
9.3.1 South America Deep Learning in Healthcare Consumption Value by Country (2019-2030)
9.3.2 Brazil Deep Learning in Healthcare Market Size and Forecast (2019-2030)
9.3.3 Argentina Deep Learning in Healthcare Market Size and Forecast (2019-2030)
10.1 Middle East & Africa Deep Learning in Healthcare Consumption Value by Type (2019-2030)
10.2 Middle East & Africa Deep Learning in Healthcare Consumption Value by Application (2019-2030)
10.3 Middle East & Africa Deep Learning in Healthcare Market Size by Country
10.3.1 Middle East & Africa Deep Learning in Healthcare Consumption Value by Country (2019-2030)
10.3.2 Turkey Deep Learning in Healthcare Market Size and Forecast (2019-2030)
10.3.3 Saudi Arabia Deep Learning in Healthcare Market Size and Forecast (2019-2030)
10.3.4 UAE Deep Learning in Healthcare Market Size and Forecast (2019-2030)
11.1 Deep Learning in Healthcare Market Drivers
11.2 Deep Learning in Healthcare Market Restraints
11.3 Deep Learning in Healthcare Trends Analysis
11.4 Porters Five Forces Analysis
11.4.1 Threat of New Entrants
11.4.2 Bargaining Power of Suppliers
11.4.3 Bargaining Power of Buyers
11.4.4 Threat of Substitutes
11.4.5 Competitive Rivalry
12.1 Deep Learning in Healthcare Industry Chain
12.2 Deep Learning in Healthcare Upstream Analysis
12.3 Deep Learning in Healthcare Midstream Analysis
12.4 Deep Learning in Healthcare Downstream Analysis
14.1 Methodology
14.2 Research Process and Data Source
14.3 Disclaimer
Table of Figures
List of Tables
Table 1. Global Deep Learning in Healthcare Consumption Value by Type, (USD Million), 2019 & 2023 & 2030
Table 2. Global Deep Learning in Healthcare Consumption Value by Application, (USD Million), 2019 & 2023 & 2030
Table 3. Global Deep Learning in Healthcare Consumption Value by Region (2019-2024) & (USD Million)
Table 4. Global Deep Learning in Healthcare Consumption Value by Region (2025-2030) & (USD Million)
Table 5. NVIDIA (US) Company Information, Head Office, and Major Competitors
Table 6. NVIDIA (US) Major Business
Table 7. NVIDIA (US) Deep Learning in Healthcare Product and Solutions
Table 8. NVIDIA (US) Deep Learning in Healthcare Revenue (USD Million), Gross Margin and Market Share (2019-2024)
Table 9. NVIDIA (US) Recent Developments and Future Plans
Table 10. Intel (US) Company Information, Head Office, and Major Competitors
Table 11. Intel (US) Major Business
Table 12. Intel (US) Deep Learning in Healthcare Product and Solutions
Table 13. Intel (US) Deep Learning in Healthcare Revenue (USD Million), Gross Margin and Market Share (2019-2024)
Table 14. Intel (US) Recent Developments and Future Plans
Table 15. Xilinx (US) Company Information, Head Office, and Major Competitors
Table 16. Xilinx (US) Major Business
Table 17. Xilinx (US) Deep Learning in Healthcare Product and Solutions
Table 18. Xilinx (US) Deep Learning in Healthcare Revenue (USD Million), Gross Margin and Market Share (2019-2024)
Table 19. Xilinx (US) Recent Developments and Future Plans
Table 20. Samsung Electronics (South Korea) Company Information, Head Office, and Major Competitors
Table 21. Samsung Electronics (South Korea) Major Business
Table 22. Samsung Electronics (South Korea) Deep Learning in Healthcare Product and Solutions
Table 23. Samsung Electronics (South Korea) Deep Learning in Healthcare Revenue (USD Million), Gross Margin and Market Share (2019-2024)
Table 24. Samsung Electronics (South Korea) Recent Developments and Future Plans
Table 25. Micron Technology (US) Company Information, Head Office, and Major Competitors
Table 26. Micron Technology (US) Major Business
Table 27. Micron Technology (US) Deep Learning in Healthcare Product and Solutions
Table 28. Micron Technology (US) Deep Learning in Healthcare Revenue (USD Million), Gross Margin and Market Share (2019-2024)
Table 29. Micron Technology (US) Recent Developments and Future Plans
Table 30. Qualcomm (US) Company Information, Head Office, and Major Competitors
Table 31. Qualcomm (US) Major Business
Table 32. Qualcomm (US) Deep Learning in Healthcare Product and Solutions
Table 33. Qualcomm (US) Deep Learning in Healthcare Revenue (USD Million), Gross Margin and Market Share (2019-2024)
Table 34. Qualcomm (US) Recent Developments and Future Plans
Table 35. IBM (US) Company Information, Head Office, and Major Competitors
Table 36. IBM (US) Major Business
Table 37. IBM (US) Deep Learning in Healthcare Product and Solutions
Table 38. IBM (US) Deep Learning in Healthcare Revenue (USD Million), Gross Margin and Market Share (2019-2024)
Table 39. IBM (US) Recent Developments and Future Plans
Table 40. Google (US) Company Information, Head Office, and Major Competitors
Table 41. Google (US) Major Business
Table 42. Google (US) Deep Learning in Healthcare Product and Solutions
Table 43. Google (US) Deep Learning in Healthcare Revenue (USD Million), Gross Margin and Market Share (2019-2024)
Table 44. Google (US) Recent Developments and Future Plans
Table 45. Microsoft (US) Company Information, Head Office, and Major Competitors
Table 46. Microsoft (US) Major Business
Table 47. Microsoft (US) Deep Learning in Healthcare Product and Solutions
Table 48. Microsoft (US) Deep Learning in Healthcare Revenue (USD Million), Gross Margin and Market Share (2019-2024)
Table 49. Microsoft (US) Recent Developments and Future Plans
Table 50. AWS (US) Company Information, Head Office, and Major Competitors
Table 51. AWS (US) Major Business
Table 52. AWS (US) Deep Learning in Healthcare Product and Solutions
Table 53. AWS (US) Deep Learning in Healthcare Revenue (USD Million), Gross Margin and Market Share (2019-2024)
Table 54. AWS (US) Recent Developments and Future Plans
Table 55. Graphcore (UK) Company Information, Head Office, and Major Competitors
Table 56. Graphcore (UK) Major Business
Table 57. Graphcore (UK) Deep Learning in Healthcare Product and Solutions
Table 58. Graphcore (UK) Deep Learning in Healthcare Revenue (USD Million), Gross Margin and Market Share (2019-2024)
Table 59. Graphcore (UK) Recent Developments and Future Plans
Table 60. Mythic (US) Company Information, Head Office, and Major Competitors
Table 61. Mythic (US) Major Business
Table 62. Mythic (US) Deep Learning in Healthcare Product and Solutions
Table 63. Mythic (US) Deep Learning in Healthcare Revenue (USD Million), Gross Margin and Market Share (2019-2024)
Table 64. Mythic (US) Recent Developments and Future Plans
Table 65. Adapteva (US) Company Information, Head Office, and Major Competitors
Table 66. Adapteva (US) Major Business
Table 67. Adapteva (US) Deep Learning in Healthcare Product and Solutions
Table 68. Adapteva (US) Deep Learning in Healthcare Revenue (USD Million), Gross Margin and Market Share (2019-2024)
Table 69. Adapteva (US) Recent Developments and Future Plans
Table 70. Koniku (US) Company Information, Head Office, and Major Competitors
Table 71. Koniku (US) Major Business
Table 72. Koniku (US) Deep Learning in Healthcare Product and Solutions
Table 73. Koniku (US) Deep Learning in Healthcare Revenue (USD Million), Gross Margin and Market Share (2019-2024)
Table 74. Koniku (US) Recent Developments and Future Plans
Table 75. Global Deep Learning in Healthcare Revenue (USD Million) by Players (2019-2024)
Table 76. Global Deep Learning in Healthcare Revenue Share by Players (2019-2024)
Table 77. Breakdown of Deep Learning in Healthcare by Company Type (Tier 1, Tier 2, and Tier 3)
Table 78. Market Position of Players in Deep Learning in Healthcare, (Tier 1, Tier 2, and Tier 3), Based on Revenue in 2023
Table 79. Head Office of Key Deep Learning in Healthcare Players
Table 80. Deep Learning in Healthcare Market: Company Product Type Footprint
Table 81. Deep Learning in Healthcare Market: Company Product Application Footprint
Table 82. Deep Learning in Healthcare New Market Entrants and Barriers to Market Entry
Table 83. Deep Learning in Healthcare Mergers, Acquisition, Agreements, and Collaborations
Table 84. Global Deep Learning in Healthcare Consumption Value (USD Million) by Type (2019-2024)
Table 85. Global Deep Learning in Healthcare Consumption Value Share by Type (2019-2024)
Table 86. Global Deep Learning in Healthcare Consumption Value Forecast by Type (2025-2030)
Table 87. Global Deep Learning in Healthcare Consumption Value by Application (2019-2024)
Table 88. Global Deep Learning in Healthcare Consumption Value Forecast by Application (2025-2030)
Table 89. North America Deep Learning in Healthcare Consumption Value by Type (2019-2024) & (USD Million)
Table 90. North America Deep Learning in Healthcare Consumption Value by Type (2025-2030) & (USD Million)
Table 91. North America Deep Learning in Healthcare Consumption Value by Application (2019-2024) & (USD Million)
Table 92. North America Deep Learning in Healthcare Consumption Value by Application (2025-2030) & (USD Million)
Table 93. North America Deep Learning in Healthcare Consumption Value by Country (2019-2024) & (USD Million)
Table 94. North America Deep Learning in Healthcare Consumption Value by Country (2025-2030) & (USD Million)
Table 95. Europe Deep Learning in Healthcare Consumption Value by Type (2019-2024) & (USD Million)
Table 96. Europe Deep Learning in Healthcare Consumption Value by Type (2025-2030) & (USD Million)
Table 97. Europe Deep Learning in Healthcare Consumption Value by Application (2019-2024) & (USD Million)
Table 98. Europe Deep Learning in Healthcare Consumption Value by Application (2025-2030) & (USD Million)
Table 99. Europe Deep Learning in Healthcare Consumption Value by Country (2019-2024) & (USD Million)
Table 100. Europe Deep Learning in Healthcare Consumption Value by Country (2025-2030) & (USD Million)
Table 101. Asia-Pacific Deep Learning in Healthcare Consumption Value by Type (2019-2024) & (USD Million)
Table 102. Asia-Pacific Deep Learning in Healthcare Consumption Value by Type (2025-2030) & (USD Million)
Table 103. Asia-Pacific Deep Learning in Healthcare Consumption Value by Application (2019-2024) & (USD Million)
Table 104. Asia-Pacific Deep Learning in Healthcare Consumption Value by Application (2025-2030) & (USD Million)
Table 105. Asia-Pacific Deep Learning in Healthcare Consumption Value by Region (2019-2024) & (USD Million)
Table 106. Asia-Pacific Deep Learning in Healthcare Consumption Value by Region (2025-2030) & (USD Million)
Table 107. South America Deep Learning in Healthcare Consumption Value by Type (2019-2024) & (USD Million)
Table 108. South America Deep Learning in Healthcare Consumption Value by Type (2025-2030) & (USD Million)
Table 109. South America Deep Learning in Healthcare Consumption Value by Application (2019-2024) & (USD Million)
Table 110. South America Deep Learning in Healthcare Consumption Value by Application (2025-2030) & (USD Million)
Table 111. South America Deep Learning in Healthcare Consumption Value by Country (2019-2024) & (USD Million)
Table 112. South America Deep Learning in Healthcare Consumption Value by Country (2025-2030) & (USD Million)
Table 113. Middle East & Africa Deep Learning in Healthcare Consumption Value by Type (2019-2024) & (USD Million)
Table 114. Middle East & Africa Deep Learning in Healthcare Consumption Value by Type (2025-2030) & (USD Million)
Table 115. Middle East & Africa Deep Learning in Healthcare Consumption Value by Application (2019-2024) & (USD Million)
Table 116. Middle East & Africa Deep Learning in Healthcare Consumption Value by Application (2025-2030) & (USD Million)
Table 117. Middle East & Africa Deep Learning in Healthcare Consumption Value by Country (2019-2024) & (USD Million)
Table 118. Middle East & Africa Deep Learning in Healthcare Consumption Value by Country (2025-2030) & (USD Million)
Table 119. Deep Learning in Healthcare Raw Material
Table 120. Key Suppliers of Deep Learning in Healthcare Raw Materials
List of Figures
Figure 1. Deep Learning in Healthcare Picture
Figure 2. Global Deep Learning in Healthcare Consumption Value by Type, (USD Million), 2019 & 2023 & 2030
Figure 3. Global Deep Learning in Healthcare Consumption Value Market Share by Type in 2023
Figure 4. Hardware
Figure 5. Software
Figure 6. Service
Figure 7. Global Deep Learning in Healthcare Consumption Value by Type, (USD Million), 2019 & 2023 & 2030
Figure 8. Deep Learning in Healthcare Consumption Value Market Share by Application in 2023
Figure 9. Patient Data & Risk Analysis Picture
Figure 10. Lifestyle Management & Monitoring Picture
Figure 11. Precision Medicine Picture
Figure 12. Inpatient Care & Hospital Management Picture
Figure 13. Medical Imaging & Diagnostics Picture
Figure 14. Drug Discovery Picture
Figure 15. Other Picture
Figure 16. Global Deep Learning in Healthcare Consumption Value, (USD Million): 2019 & 2023 & 2030
Figure 17. Global Deep Learning in Healthcare Consumption Value and Forecast (2019-2030) & (USD Million)
Figure 18. Global Market Deep Learning in Healthcare Consumption Value (USD Million) Comparison by Region (2019 & 2023 & 2030)
Figure 19. Global Deep Learning in Healthcare Consumption Value Market Share by Region (2019-2030)
Figure 20. Global Deep Learning in Healthcare Consumption Value Market Share by Region in 2023
Figure 21. North America Deep Learning in Healthcare Consumption Value (2019-2030) & (USD Million)
Figure 22. Europe Deep Learning in Healthcare Consumption Value (2019-2030) & (USD Million)
Figure 23. Asia-Pacific Deep Learning in Healthcare Consumption Value (2019-2030) & (USD Million)
Figure 24. South America Deep Learning in Healthcare Consumption Value (2019-2030) & (USD Million)
Figure 25. Middle East and Africa Deep Learning in Healthcare Consumption Value (2019-2030) & (USD Million)
Figure 26. Global Deep Learning in Healthcare Revenue Share by Players in 2023
Figure 27. Deep Learning in Healthcare Market Share by Company Type (Tier 1, Tier 2 and Tier 3) in 2023
Figure 28. Global Top 3 Players Deep Learning in Healthcare Market Share in 2023
Figure 29. Global Top 6 Players Deep Learning in Healthcare Market Share in 2023
Figure 30. Global Deep Learning in Healthcare Consumption Value Share by Type (2019-2024)
Figure 31. Global Deep Learning in Healthcare Market Share Forecast by Type (2025-2030)
Figure 32. Global Deep Learning in Healthcare Consumption Value Share by Application (2019-2024)
Figure 33. Global Deep Learning in Healthcare Market Share Forecast by Application (2025-2030)
Figure 34. North America Deep Learning in Healthcare Consumption Value Market Share by Type (2019-2030)
Figure 35. North America Deep Learning in Healthcare Consumption Value Market Share by Application (2019-2030)
Figure 36. North America Deep Learning in Healthcare Consumption Value Market Share by Country (2019-2030)
Figure 37. United States Deep Learning in Healthcare Consumption Value (2019-2030) & (USD Million)
Figure 38. Canada Deep Learning in Healthcare Consumption Value (2019-2030) & (USD Million)
Figure 39. Mexico Deep Learning in Healthcare Consumption Value (2019-2030) & (USD Million)
Figure 40. Europe Deep Learning in Healthcare Consumption Value Market Share by Type (2019-2030)
Figure 41. Europe Deep Learning in Healthcare Consumption Value Market Share by Application (2019-2030)
Figure 42. Europe Deep Learning in Healthcare Consumption Value Market Share by Country (2019-2030)
Figure 43. Germany Deep Learning in Healthcare Consumption Value (2019-2030) & (USD Million)
Figure 44. France Deep Learning in Healthcare Consumption Value (2019-2030) & (USD Million)
Figure 45. United Kingdom Deep Learning in Healthcare Consumption Value (2019-2030) & (USD Million)
Figure 46. Russia Deep Learning in Healthcare Consumption Value (2019-2030) & (USD Million)
Figure 47. Italy Deep Learning in Healthcare Consumption Value (2019-2030) & (USD Million)
Figure 48. Asia-Pacific Deep Learning in Healthcare Consumption Value Market Share by Type (2019-2030)
Figure 49. Asia-Pacific Deep Learning in Healthcare Consumption Value Market Share by Application (2019-2030)
Figure 50. Asia-Pacific Deep Learning in Healthcare Consumption Value Market Share by Region (2019-2030)
Figure 51. China Deep Learning in Healthcare Consumption Value (2019-2030) & (USD Million)
Figure 52. Japan Deep Learning in Healthcare Consumption Value (2019-2030) & (USD Million)
Figure 53. South Korea Deep Learning in Healthcare Consumption Value (2019-2030) & (USD Million)
Figure 54. India Deep Learning in Healthcare Consumption Value (2019-2030) & (USD Million)
Figure 55. Southeast Asia Deep Learning in Healthcare Consumption Value (2019-2030) & (USD Million)
Figure 56. Australia Deep Learning in Healthcare Consumption Value (2019-2030) & (USD Million)
Figure 57. South America Deep Learning in Healthcare Consumption Value Market Share by Type (2019-2030)
Figure 58. South America Deep Learning in Healthcare Consumption Value Market Share by Application (2019-2030)
Figure 59. South America Deep Learning in Healthcare Consumption Value Market Share by Country (2019-2030)
Figure 60. Brazil Deep Learning in Healthcare Consumption Value (2019-2030) & (USD Million)
Figure 61. Argentina Deep Learning in Healthcare Consumption Value (2019-2030) & (USD Million)
Figure 62. Middle East and Africa Deep Learning in Healthcare Consumption Value Market Share by Type (2019-2030)
Figure 63. Middle East and Africa Deep Learning in Healthcare Consumption Value Market Share by Application (2019-2030)
Figure 64. Middle East and Africa Deep Learning in Healthcare Consumption Value Market Share by Country (2019-2030)
Figure 65. Turkey Deep Learning in Healthcare Consumption Value (2019-2030) & (USD Million)
Figure 66. Saudi Arabia Deep Learning in Healthcare Consumption Value (2019-2030) & (USD Million)
Figure 67. UAE Deep Learning in Healthcare Consumption Value (2019-2030) & (USD Million)
Figure 68. Deep Learning in Healthcare Market Drivers
Figure 69. Deep Learning in Healthcare Market Restraints
Figure 70. Deep Learning in Healthcare Market Trends
Figure 71. Porters Five Forces Analysis
Figure 72. Manufacturing Cost Structure Analysis of Deep Learning in Healthcare in 2023
Figure 73. Manufacturing Process Analysis of Deep Learning in Healthcare
Figure 74. Deep Learning in Healthcare Industrial Chain
Figure 75. Methodology
Figure 76. Research Process and Data Source
Research Methodology
Client Requirements
Review and analyze client requirements
Discussion of all the project requirements and queries
Flexibility Check
Project Feasibility Analysis
Finalizing tentative research programme
Structuring project proposal with scope, timeline, and costs
Analyzing Market Dynamics
Determination of key drivers, restraints, challenge, and opportunity
Identifies market needs and trends
Market Size Estimation & Forecast
Estimation of historical data based on secondary and primary data
Anticipating market recast by assigning weightage to market forces (drivers, restraints, opportunities)
Freezing historical and forecast market size estimations based on evolution, trends, outlook, and strategies
Consideration of geography, region-specific product/service demand for region segments
Consideration of product utilization rates, product demand outlook for segments by application or end-user.
Data Source
Secondary Source
Data collections from annual reports, presentations,associations, journals, analyst reports,
paid database, press releases, blogs, newsletters,and GIR repositories.
Primary Source
Research discussion with manufacturers, distributors, suppliers, end user, industry experts
to verify insights.
Validation
and
triangulation of
secondary and primary source.
Collection of data
Cumulating and collating the essential qualitative and quantitative data
Generation of report in client requested format by research analysts
Reviews by expert analysts
Final quality check
Clarifying queries
Receiving feedback
Ensuring satisfaction
01 Identification of data
This step involves identification of several primary and secondary data research sources, including Global Info Research's internal data sources. The primary sources consist of in-depth discussions and interviews with policy makers, industry experts, and data evaluators, whereas secondary sources include a thorough study of market journals, press releases, annual reports, and government and non-government agencies websites.
-
02 Evaluation of Market Dynamic
This phase includes a detailed evaluation of several factors that are likely to affect the market dynamics. It involves a comprehensive assessment of major market pain points, drivers, and trends. It also comprises a detailed study of research plans and methodology.
-
03 Collection of Data
This process consists of gathering data, accessing proprietary databases, and reaching out to key industry participants that operate in the market across the value chain. It also involves studying several patterns in the historical data and comparing it with the current scenario.
-
04 Collaboration of Data
This stage involves the validation of data and arrival at actual statistics, and evolution of the market over the years. It entails the study and analyzes various segments and verticals of the market. An impact analysis is also performed to observe which factors will affect the market in the next few years.
05 Verification and Analysis
This is the final stage, which involves both quantity and quality checks. Although the process of data verification is an integral part of the research process, all data points and statistics and figures are re-checked to uphold their authenticity and validity.
Companies Mentioned
NVIDIA (US) Intel (US) Xilinx (US) Samsung Electronics (South Korea) Micron Technology (US) Qualcomm (US) IBM (US) Google (US) Microsoft (US) AWS (US) Graphcore (UK) Mythic (US) Adapteva (US) Koniku (US)
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