2024 Fiscal Year Final Research Report
Machine learning models for predicting cognitive decline based on long-term longitudinal data
| Project/Area Number |
22K10074
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Multi-year Fund |
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| Section | 一般 |
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| Review Section |
Basic Section 57050:Prosthodontics-related
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| Research Institution | Osaka University |
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Principal Investigator |
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| Co-Investigator(Kenkyū-buntansha) |
野崎 一徳 大阪大学, 歯学部附属病院, 准教授 (40379110)
豆野 智昭 大阪大学, 大学院歯学研究科, 助教 (50845922)
八田 昂大 大阪大学, 大学院歯学研究科, 招へい教員 (60845949)
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| Project Period (FY) |
2022-04-01 – 2025-03-31
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| Keywords | 高齢者 |
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| Outline of Final Research Achievements |
As our country enters a super-aged society, it is crucial to predict the onset of diseases that lead to the need for long-term care, as well as their risk factors, for each elderly individual. By doing so, appropriate measures can be implemented to help as many elderly people as possible maintain independent lives.
With this in mind, we focused on dementia, which is a major cause of the need for long-term care. Based on the hypothesis that "if the onset of dementia can be predicted from oral conditions, preventive care can be achieved through dental approaches," we aim to develop a machine learning model to predict Cognitive declin. This model will be built using data from a 12-year longitudinal study involving 3,000 participants and analyzing a vast number of factors, including oral health conditions.
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| Free Research Field |
高齢者歯科学
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| Academic Significance and Societal Importance of the Research Achievements |
本研究で作成する認知機能低下予測モデルは，健康長寿の要因を探るため10年以上にわたり，3000名もの学際的な大規模長期縦断調査，老年学研究により得られた身体的因子，社会的因子，心理的因子のデータに，口腔因子（残存歯数や歯周病の状態など）や口腔機能（咬合力や唾液分泌機能など）のデータを加えた包括的なデータに基づいたものである.
したがって，本研究で作成された予測モデルは，口腔に関するデータ以外も考慮されているだけでなく，これまでにない長期的な予測が可能な信頼性の高い予測モデルであると思われる.
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