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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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Principais autores: Jing-Hong Xiao, Hsiao-Yen Kang, Li-Ching Wu, Tien Hsu, Chin-Pyng Wu, Li-Jen Su
Format: Artigo
Sprog:Inglês
Udgivet: Frontiers Media S.A. 2025-12-01
Serier:Frontiers in Genetics
Fag:
type 2 diabetes
genome-wide association studies
machine learning
algorithmic rules
disease risk prediction
Online adgang:https://www.frontiersin.org/articles/10.3389/fgene.2025.1694084/full
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