Report ID : AMR1004203 | Industries : ICT | Published On :December 2023 | Page Count : 224
Global AI Training Dataset in Healthcare Market Size, Trends, and Growth Opportunity, By Model (Text, Image/Video), By Dataset Type (Electronic Health Records, Medical Imaging, Wearable Devices, Telemedicine, and Others), By Region and forecast till 2030.
Global AI Training Dataset in Healthcare Market
Global AI Training Dataset in Healthcare Market was valued at USD 340 million in 2022 and is slated to reach USD 1450 million by 2030 at a CAGR of 22.1% from 2023-2030.
The global Ai training dataset in healthcare is a large collection of different medical data that includes medical photographs, electronic health records, genomic data, pharmaceutical data, wearable device records, and medical literature. These datasets are critical for training artificial intelligence models in healthcare, allowing them to diagnose diseases, forecast outcomes, and aid in a variety of medical tasks.
Market Drivers
The factors driving the creation and use of Global AI Training Datasets in Healthcare are several. To begin with, the rising availability of electronic health records and medical imaging data has made it easier to create comprehensive datasets. Second, increased investment in AI research and healthcare technologies has sped up dataset development. Furthermore, the demand for high-quality training data has been driven by the need for more accurate disease detection, therapy tailoring, and drug development. Furthermore, legislative advances and data-sharing programs have fostered collaboration. These factors all work together to assist the development of AI training datasets that will enable AI models to improve healthcare outcomes and patient care.
Market Restraints
The exchange and use of sensitive healthcare data is restricted due to privacy concerns and severe data protection requirements. Large, representative datasets can be expensive and time-consuming to obtain and curate. Ethical constraints and inherent biases in data bring further obstacles. Furthermore, maintaining the accuracy and integrity of the data is an ongoing challenge. These constraints impede AI's general acceptance and efficacy in healthcare.
Impact of COVID-19
The COVID-19 pandemic hampered the collecting of healthcare data for AI training datasets. It resulted in an increase in demand for AI solutions, underlining the need for additional data, but it also presented difficulties in preserving data quality and protecting data privacy. Remote patient monitoring and telehealth data have grown in importance, but in-person data collection has been hampered, influencing the nature and size of AI training datasets in healthcare.
Recent Development
In July 2023, AWS HealthScribe, a HIPAA-compliant service, streamlines clinical documentation with speech recognition and generative AI for healthcare software. It provides a unified API for automatic transcript generation, info extraction, and summary creation from patient-doctor talks. This simplifies AI integration into healthcare apps for specialties like general medicine and orthopedics, without the need for managing ML infrastructure. It ensures responsible AI deployment by attributing text sources for physician review before entering the EHR.
Market Segmentation
Global AI Training Dataset in Healthcare Market is segmented into model and dataset type. By model such as text, image/video. By dataset type such as electronic health records, medical imaging, wearable devices, telemedicine, and others.
Regional Analysis
Global AI Training Dataset in Healthcare Market is segmented into five regions Americas, Europe, Asia-Pacific, and the Middle East & Africa. The North American market dominated during the projection period. The deployment of customized medicine is a big development in this region, and AI training datasets are evolving to include genomic information. These datasets link an individual's genetic profile with clinical data, allowing AI models capable of offering individualized treatment recommendations and predicting disease predisposition based on genetics to be created. The emphasis on precision medicine and genomics research in North America emphasizes the usefulness of datasets that combine clinical and genomic data to provide more personalized healthcare solutions.
Key Players
This report includes a list of numerous Key Players, namely Alegion, Amazon Web Services, Inc., Appen Limited, Cogito Tech LLC, Deep Vision Data, Google, LLC (Kaggle), Lionbridge Technologies, Inc., Microsoft Corporation, Samasource Inc., and Scale AI, Inc.
Market Taxonomy
By Model
• Text
• Image/Video
By Dataset Type
• Electronic Health Records
• Medical Imaging
• Wearable Devices
• Telemedicine
• Others
By Region
• North America
o U.S.
o Canada
o Mexico
• Latin America
o Brazil
o Argentina
o Colombia
o Peru
o Chile
o Venezuela
o Rest of Latin America
• Europe
o Germany
o France
o UK
o Russia
o Italy
o Spain
o Rest of Europe
• Asia Pacific
o China
o Japan
o India
o South Korea
o Australia
o New Zealand
o Singapore
o Malaysia
o Rest of Asia Pacific
• Middle East & Africa
o Saudi Arabia
o UAE
o Egypt
o Kuwait
o South Africa
o Rest Middle East & Africa
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Global AI Training Dataset in Healthcare Market
1. Introduction
1.1. Objective of the Study
1.2. Market Definition
1.3. Market Scope
2. Research Methodology
2.1. Data Mining
2.2. Validation
2.3. Primary Interviews
2.4. List of Data Sources
3. Executive Summary
4. Global AI Training Dataset in Healthcare Market Outlook
4.1. Overview
4.2. Market Dynamics
4.2.1. Drivers
4.2.2. Restraints
4.2.3. Opportunities
4.2.4. Cumulative Impact due to recent Energy Crisis
4.2.5. Cumulative Impact due to Nearing Economic Downturn
4.2.6. Post Covid-19 World Supply and Demand Conditions
4.2.7. Cumulative Impact of Russia-Ukraine Conflict
4.3. Porters Five Force Model
4.4. Value Chain Analysis
5. Global AI Training Dataset in Healthcare Market, By Model
5.1. Y-o-Y Growth Comparison, By Model
5.2. Global AI Training Dataset in Healthcare Market Share Analysis, By Model
5.3. Global AI Training Dataset in Healthcare Market Size and Forecast, By Model
5.3.1. Text
5.3.2. Image/Video
6. Global AI Training Dataset in Healthcare Market, By Dataset Type
6.1. Y-o-Y Growth Comparison, By Dataset Type
6.2. Global AI Training Dataset in Healthcare Market Share Analysis, By Dataset Type
6.3. Global AI Training Dataset in Healthcare Market Size and Forecast, By Dataset Type
6.3.1. Electronic Health Records
6.3.2. Medical Imaging
6.3.3. Wearable Devices
6.3.4. Telemedicine
6.3.5. Others
7. Global AI Training Dataset in Healthcare Market, By Region
7.1. Global AI Training Dataset in Healthcare Market Share Analysis, By Region
7.2. Global AI Training Dataset in Healthcare Market Share Analysis, By Region
7.3. Global AI Training Dataset in Healthcare Market Size and Forecast, By Region
8. North America AI Training Dataset in Healthcare Market Analysis and Forecast (2023-2030)
8.1. Introduction
8.2. North America AI Training Dataset in Healthcare Market Share Analysis, By Model
8.3. North America AI Training Dataset in Healthcare Market Share Analysis, By Dataset Type
8.4. North America AI Training Dataset in Healthcare Market Size and Forecast, By Country
8.4.1. U.S.
8.4.1.1. Market Size and Forecast, By Model
8.4.1.2. Market Size and Forecast, By Dataset Type
8.4.2. Canada
8.4.2.1. Market Size and Forecast, By Model
8.4.2.2. Market Size and Forecast, By Dataset Type
8.4.3. Mexico
8.4.3.1. Market Size and Forecast, By Model
8.4.3.2. Market Size and Forecast, By Dataset Type
9. Europe AI Training Dataset in Healthcare Market Analysis and Forecast (2023-2030)
9.1. Introduction
9.2. Europe AI Training Dataset in Healthcare Market Share Analysis, By Model
9.3. Europe AI Training Dataset in Healthcare Market Share Analysis, By Dataset Type
9.4. Europe AI Training Dataset in Healthcare Market Size and Forecast, By Country
9.4.1. Germany
9.4.1.1. Market Size and Forecast, By Model
9.4.1.2. Market Size and Forecast, By Dataset Type
9.4.2. France
9.4.2.1. Market Size and Forecast, By Model
9.4.2.2. Market Size and Forecast, By Dataset Type
9.4.3. UK
9.4.3.1. Market Size and Forecast, By Model
9.4.3.2. Market Size and Forecast, By Dataset Type
9.4.4. Russia
9.4.4.1. Market Size and Forecast, By Model
9.4.4.2. Market Size and Forecast, By Dataset Type
9.4.5. Italy
9.4.5.1. Market Size and Forecast, By Model
9.4.5.2. Market Size and Forecast, By Dataset Type
9.4.6. Spain
9.4.6.1. Market Size and Forecast, By Model
9.4.6.2. Market Size and Forecast, By Dataset Type
9.4.7. Rest of Europe
9.4.7.1. Market Size and Forecast, By Model
9.4.7.2. Market Size and Forecast, By Dataset Type
10. Asia Pacific AI Training Dataset in Healthcare Market Analysis and Forecast (2023-2030)
10.1. Introduction
10.2. Asia Pacific AI Training Dataset in Healthcare Market Share Analysis, By Model
10.3. Asia Pacific AI Training Dataset in Healthcare Market Share Analysis, By Dataset Type
10.4. Asia Pacific AI Training Dataset in Healthcare Market Size and Forecast, By Country
10.4.1. China
10.4.1.1. Market Size and Forecast, By Model
10.4.1.2. Market Size and Forecast, By Dataset Type
10.4.2. Japan
10.4.2.1. Market Size and Forecast, By Model
10.4.2.2. Market Size and Forecast, By Dataset Type
10.4.3. India
10.4.3.1. Market Size and Forecast, By Model
10.4.3.2. Market Size and Forecast, By Dataset Type
10.4.4. South Korea
10.4.4.1. Market Size and Forecast, By Model
10.4.4.2. Market Size and Forecast, By Dataset Type
10.4.5. Australia
10.4.5.1. Market Size and Forecast, By Model
10.4.5.2. Market Size and Forecast, By Dataset Type
10.4.6. New Zealand
10.4.6.1. Market Size and Forecast, By Model
10.4.6.2. Market Size and Forecast, By Dataset Type
10.4.7. Singapore
10.4.7.1. Market Size and Forecast, By Model
10.4.7.2. Market Size and Forecast, By Dataset Type
10.4.8. Malaysia
10.4.8.1. Market Size and Forecast, By Model
10.4.8.2. Market Size and Forecast, By Dataset Type
10.4.9. Rest of Asia
10.4.9.1. Market Size and Forecast, By Model
10.4.9.2. Market Size and Forecast, By Dataset Type
11. Latin America AI Training Dataset in Healthcare Market Analysis and Forecast (2023-2030)
11.1. Introduction
11.2. Latin America AI Training Dataset in Healthcare Market Share Analysis, By Model
11.3. Latin America AI Training Dataset in Healthcare Market Share Analysis, By Dataset Type
11.4. Latin America AI Training Dataset in Healthcare Market Size and Forecast, Country
11.4.1. Brazil
11.4.1.1. Market Size and Forecast, By Model
11.4.1.2. Market Size and Forecast, By Dataset Type
11.4.2. Argentina
11.4.2.1. Market Size and Forecast, By Model
11.4.2.2. Market Size and Forecast, By Dataset Type
11.4.3. Colombia
11.4.3.1. Market Size and Forecast, By Model
11.4.3.2. Market Size and Forecast, By Dataset Type
11.4.4. Peru
11.4.4.1. Market Size and Forecast, By Model
11.4.4.2. Market Size and Forecast, By Dataset Type
11.4.5. Chile
11.4.5.1. Market Size and Forecast, By Model
11.4.5.2. Market Size and Forecast, By Dataset Type
11.4.6. Venezuela
11.4.6.1. Market Size and Forecast, By Model
11.4.6.2. Market Size and Forecast, By Dataset Type
11.4.7. Rest of Latin America
11.4.7.1. Market Size and Forecast, By Model
11.4.7.2. Market Size and Forecast, By Dataset Type
12. Middle East AI Training Dataset in Healthcare Market Analysis and Forecast (2023-2030)
12.1. Introduction
12.2. Middle East AI Training Dataset in Healthcare Market Share Analysis, By Model
12.3. Middle East AI Training Dataset in Healthcare Market Size and Forecast, By Dataset Type
12.4. Middle East AI Training Dataset in Healthcare Market Size and Forecast, By Country
12.4.1. Saudi Arabia
12.4.1.1. Market Size and Forecast, By Model
12.4.1.2. Market Size and Forecast, By Dataset Type
12.4.2. UAE
12.4.2.1. Market Size and Forecast, By Model
12.4.2.2. Market Size and Forecast, By Dataset Type
12.4.3. Egypt
12.4.3.1. Market Size and Forecast, By Model
12.4.3.2. Market Size and Forecast, By Dataset Type
12.4.4. Kuwait
12.4.4.1. Market Size and Forecast, By Model
12.4.4.2. Market Size and Forecast, By Dataset Type
12.4.5. South Africa
12.4.5.1. Market Size and Forecast, By Model
12.4.5.2. Market Size and Forecast, By Dataset Type
12.4.6. Rest of Middle East & Africa
12.4.6.1. Market Size and Forecast, By Model
12.4.6.2. Market Size and Forecast, By Dataset Type
13. Competitive Analysis
13.1. Competition Dashboard
13.2. Market share Analysis of Top Vendors
13.3. Key Development Strategies
14. Company Profiles
14.1. Alegion
14.1.1. Offerings
14.1.2. Key Financials
14.1.3. Business Segment & Geographic Overview
14.1.4. Key Market Developments
14.1.5. Key Strategies
14.2. Amazon Web Services, Inc.
14.2.1. Overview
14.2.2. Offerings
14.2.3. Key Financials
14.2.4. Business Segment & Geographic Overview
14.2.5. Key Market Developments
14.2.6. Key Strategies
14.3. Appen Limited
14.3.1. Overview
14.3.2. Offerings
14.3.3. Key Financials
14.3.4. Business Segment & Geographic Overview
14.3.5. Key Market Developments
14.3.6. Key Strategies
14.4. Cogito Tech LLC
14.4.1. Overview
14.4.2. Offerings
14.4.3. Key Financials
14.4.4. Business Segment & Geographic Overview
14.4.5. Key Market Developments
14.4.6. Key Strategies
14.5. Deep Vision Data
14.5.1. Overview
14.5.2. Offerings
14.5.3. Key Financials
14.5.4. Business Segment & Geographic Overview
14.5.5. Key Market Developments
14.5.6. Key Strategies
14.6. Google, LLC (Kaggle)
14.6.1. Overview
14.6.2. Offerings
14.6.3. Key Financials
14.6.4. Business Segment & Geographic Overview
14.6.5. Key Market Developments
14.6.6. Key Strategies
14.7. Lionbridge Technologies, Inc.
14.7.1. Overview
14.7.2. Offerings
14.7.3. Key Financials
14.7.4. Business Segment & Geographic Overview
14.7.5. Key Market Developments
14.7.6. Key Strategies
14.8. Microsoft Corporation
14.8.1. Overview
14.8.2. Offerings
14.8.3. Key Financials
14.8.4. Business Segment & Geographic Overview
14.8.5. Key Market Developments
14.8.6. Key Strategies
14.9. Samasource Inc.
14.9.1. Overview
14.9.2. Offerings
14.9.3. Key Financials
14.9.4. Business Segment & Geographic Overview
14.9.5. Key Market Developments
14.9.6. Key Strategies
14.10. Scale AI, Inc.
14.10.1. Overview
14.10.2. Offerings
14.10.3. Key Financials
14.10.4. Business Segment & Geographic Overview
14.10.5. Key Market Developments
14.10.6. Key Strategies
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