Development and dissemination of AI-based innovative health guidance for life-style-related disease

Project Gist

Supporting present and future health with health data and epidemiology.

Keywords

Clinical Epidemiology, Data Science, Learning Health System

Background and Purpose

Health issues are changing and becoming more complex due to internal shocks such as a low birthrate and aging population, and external shocks such as disaster and the spread of infection. Health data is expected to be used to support health now and in the future. Clinical epidemiology and related academic disciplines will work together to support population health by properly analyzing and interpreting large, broad health data and designing interventions.

Project Achievements

We integrated clinical epidemiology with related academic disciplines such as informatics and behavioral economics. We developed a model of a learning health system that identifies health issues from health data and implements interventions for improvement. In addition, we designed a scheme for social implementation by working with insurers and industries that support health services.

Future Prospects

We will continue to challenge the limits of current methodologies and exceed those limits to explore what contribution we can make to society by applying clinical epidemiology to health data in the medical field.

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Principal Investigator