第234回白眉セミナー ： 『高ベネフィットアプローチ：次世代の個別化医療における機械学習を用いた効果の異質性評価』
- 井上 浩輔（第13期 医学研究科 特定准教授）
- 2023/09/05 4:45pm
- Zoomおよび学術研究支援棟地下会議室1＆2
- 英語
- オンサイトおよびZoom
要旨
In medicine, clinicians treat individuals with a high risk of diseases under an implicit assumption that risk is correlated with benefit. However, high-risk patients are not always the ones who benefit most from the treatment, and treating individuals with the highest estimated “benefit” (rather than “risk”) may improve population health outcomes. In this presentation, I will introduce a state-of-the-art machine learning algorithm to assess heterogeneity by predicting the treatment effect at individual levels. Then I will share the concept (“high-benefit approach”) and application examples to maximize the effectiveness of treatment and resource allocation toward future precision medicine.