High-Resolution Digital Phenotypes From Consumer Wearables and Their Applications in Machine Learning of Cardiometabolic Risk Markers: Cohort Study.

Weizhuang Zhou, Yu En Chan,Chuan Sheng Foo, Jingxian Zhang,Jing Xian Teo,Sonia Davila,Weiting Huang,Jonathan Yap,Stuart Cook, Patrick Tan,Calvin Woon-Loong Chin,Khung Keong Yeo,Weng Khong Lim,Pavitra Krishnaswamy

Journal of medical Internet research（2022）

引用 4|浏览18

暂无评分

摘要

High-resolution digital phenotypes recorded by consumer wearables in free-living states have the potential to enhance the prediction of cardiometabolic disease risk and could enable more proactive and personalized health management.

查看译文

关键词

cardiometabolic disease,digital phenotypes,free-living,heart rate,machine learning,polygenic risk scores,risk prediction,time series analysis,wearable device

AI 理解论文

溯源树

样例

生成溯源树，研究论文发展脉络

Chat Paper

正在生成论文摘要