Mimura Masaru, MD, PhD | Keio University; Kishimoto Taishiro, MD, PhD; Shimizu-Hirota Ryoko, MD, PhD; Horigome Toshiro, MD, PhD; Furukawa Shota, MD; Nakai Fumiya, MSc
Competition Sponsor: Japan Agency for Medical Research and Development
Awardee Year: 2024
As Japan is a superaged country, enhancing the cognitive reserve of the elderly is crucial. However, conventional disease education, which recommends healthy lifestyle habits such as exercise and diabetes prevention, has faced the challenge of low adherence due to unclear individual outcomes.Our suggested approach thrives to address these challenges by developing a prediction software that visualizes future individual cognitive functions based on daily activities.
Keio University Center for Preventive Medicine has accumulated annual health checkup data. In addition, data from cohort studies conducted at the university have also been accumulated. Using this data, we are trying to develop software that uses machine learning to estimate cognitive function five years by entering current cognitive function and lifestyle habits. In addition, by using counterfactual, the software can suggest individualized behavioral changes to see what lifestyle changes would be useful to prevent cognitive function decline. The above program is being developed as an industry-academia collaborative project between Keio University and Hitachi. We are also developing a tool with Splink to enable the elderly to perform cognitive training at home at any time using their smartphones. By using these programs, elderly people can see the risk of cognitive decline as their own and make the behavioral changes that are best for them to prevent cognitive decline. They will also be able to incorporate simple cognitive training tools into their daily lives. Keio University plans to demonstrate the effectiveness of these software programs in clinical studies and aims for early social implementation with participating companies.