DUBLIN – (BUSINESS WIRE) – January 6, 2022–
The report “Artificial Intelligence in Epidemiology Market by AI Type, Infrastructure, Deployment Model and Services 2022 – 2027” has been added to the offering of ResearchAndMarkets.com.
This report on the Global AI Epidemiology and Public Health Market provides a comprehensive assessment of the positive impact that AI technology will produce with respect to health informatics and the management of human health issues. public health care, as well as epidemiological analysis and response. The report assesses the macro factors affecting the market and the resulting need for hardware and software technology used in public healthcare and epidemiological informatics.
Macroeconomic factors include growth drivers and market challenges as well as potential areas of application and use in verticals of the public health industry. The report also provides the predicted market value of AI in the public health and epidemiology informatics market on a global and regional level. This includes core technology and AI specific technologies. The market forecast covers the period from 2022 to 2027.
Select the report results:
- Total global AI value in the epidemiology market to exceed $ 10 billion by 2027
- Linked to vaccine R&D, AI in drug discovery and risk analysis will reach $ 800 million by 2027
- AI will support various disease-related public health and safety services, such as mass notification
- EHR databases will be the foundation, but AI will leverage many sources for disease-related data aggregation
- Epidemiological predictive models will be significantly improved through advanced data analyzes and various AI tools and techniques
- AI Improves Efficiency and Effectiveness of Transforming Correlated Health Data into Meaningful Disease Information and Insights
The Center for Disease Control and Prevention views epidemiology as the study and analysis of the distribution, patterns and determinants of health conditions and diseases in defined populations. It is a cornerstone of public health and it shapes evidence-based policy decisions and practices by identifying disease risk factors and targets for preventive health care.
This includes identifying the factors involved in food and water borne illnesses contracted during travel or recreational activities, blood borne and sexually transmitted illnesses, and hospital acquired infections such as hospital acquired illnesses. Epidemiology is also interested in identifying trends and predictive capacities to prevent disease.
Artificial intelligence (AI) will increasingly be used to improve the efficiency and effectiveness of transforming the correlation of data into meaningful insights and insights. For example, machine learning has been used to collect search and location data from the web to identify potentially dangerous areas, such as restaurants involved in foodborne illness.
Combining the aggregation of data from multiple sources with machine learning and advanced analytics will dramatically improve the efficiency of predictive epidemiological models. For example, machine learning allows epidemiologists to evaluate as many variables as they want without increasing statistical error, a problem that often arises with multiple testing bias, which is a condition that occurs when each Additional testing performed on the data increases the possibility of error against a hypothetical target result.
An extremely important and high growth area for AI in epidemiology is drug discovery, safety and risk analysis, which we believe will represent a global market of $ 800 million by 2027. Of other areas of great potential for AI are disease and syndrome surveillance, infection prediction and forecasting. , population and disease incidence surveillance, and use of AI in immunization information systems. In addition to mapping vaccinations to disease incidence, the IIS will leverage AI to identify the impact of public opinion analysis and for public safety services such as mass notification .
Main topics covered:
Technology and application analysis
- Hardware technology analysis
- Software technology analysis
- AI technology analysis
- Enable technology analysis
- Application analysis
- Industry use case analysis
- Abbott Computing
- Agilent Technologies
- Health Allscripts
- Autoscribe Computing
- Cerner Corporation
- Changing health care
- CureMD Health
- e-Mds Inc.
- Epic systems
- GE Healthcare
- Green Lane Health
- Micronic Technology
- NextGen Health
- Optum inc.
- Philips Health
Market Analysis and Forecast 2022 – 2027
Conclusions and Recommendations
For more information on this report, visit https://www.researchandmarkets.com/r/yoi7qv.
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INDUSTRY KEYWORD: SOFTWARE PHARMACEUTICAL MATERIALS HEALTH DATA MANAGEMENT INFECTIOUS DISEASES TECHNOLOGY OTHER TECHNOLOGY
SOURCE: Research and markets
Copyright Business Wire 2022.
PUB: 06/01/2022 12: 09 / DISC: 06/01/2022 12:09
Copyright Business Wire 2022.