Integrating GWAS and machine learning for disease risk prediction in the Taiwanese Hakka population

IntroductionGenome-wide association studies (GWAS) have identified numerous loci associated with complex diseases, yet their predictive power in small or genetically homogeneous populations remains limited. Integrating machine learning with GWAS offers a path to improve risk prediction and uncover f...

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Hlavní autoři:	Jing-Hong Xiao, Hsiao-Yen Kang, Li-Ching Wu, Tien Hsu, Chin-Pyng Wu, Li-Jen Su
Médium:	Artigo
Jazyk:	Inglês
Vydáno:	Frontiers Media S.A. 2025-12-01
Edice:	Frontiers in Genetics
Témata:	type 2 diabetes genome-wide association studies machine learning algorithmic rules disease risk prediction
On-line přístup:	https://www.frontiersin.org/articles/10.3389/fgene.2025.1694084/full
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