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Article

Interpretable deep survival analysis of Alzheimer's disease via metabolic genetic variants.

Bioinformatics (Oxford, England) - 1 Jun 2026

Goo Sungwoo, Lee Soyoung, Chae Jung-Woo, Jung Sangkeun, Yun Hwi-Yeol

Abstract excerpt

BACKGROUND: Alzheimer's disease (AD) is a progressive neurodegenerative disease. Traditional models for estimating AD onset cannot capture nonlinear interactions (epistasis) among the numerous genetic variables that contribute to AD risk. METHODS: We developed a feedforward neural network (FFN)-Weibull survival model to predict AD onset using large-scale single-nucleotide polymorphism (SNP) data. We integrated an...

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PMID: 42063212
DOI: 10.1093/bioinformatics/btag213
PMCID: PMC13224968

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APOE

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PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 8 Sept 2026.

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