Hirotaka Ieki

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Machine Learning Reveals the Contribution of Rare Genetic Variants and Enhances Risk Prediction for Coronary Artery Disease in the Japanese Population

Aug 13, 2024 | medrxiv.org | Hirotaka Ieki |Kaoru Ito |Sai Zhang |Satoshi Koyama

The authors have declared no competing interest. This study was funded by the Japan Agency for Medical Research and Development (AMED) under grant numbers JP24bm1423005, JP24km0405209, JP24tm0524004, JP24tm0624002, JP24km0405209, JP24ek0210164, JP17km0305002 and JP17km0305001 and JP24tm0624002. K.I. and K.O. are supported by the Research Funding for Longevity Sciences from the NCGG (24 15).

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