Disease insights from medical data using interpretable risk prediction models

被引：0

作者：

Tang, Alice ^{[1
]}

Sirota, Marina ^{[1
]}

机构：

[1] Univ Calif San Francisco, Bakar Computat Hlth Sci Inst, San Francisco, CA 94143 USA

来源：

NATURE AGING | 2024年 / 4卷 / 03期

关键词：

D O I：

10.1038/s43587-024-00585-4

中图分类号：

Q2 [细胞生物学];

学科分类号：

071009 ; 090102 ;

摘要：

Our study demonstrates how clinical data can be used to build machine-learning models to predict the risk of Alzheimer's disease (AD) onset and can be integrated with knowledge networks to gain insights into the pathophysiology of AD, with a focus on a better understanding of disease sex differences.

引用

页码：293 / 294

页数：2

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