A correlation-based feature analysis of physical examination indicators can help predict the overall underlying health status using machine learning
Haixin Wang(University of Electronic Science and Technology of China), Lulin Huang(Sichuan Academy of Medical Sciences & Sichuan Provincial People's Hospital), Yuping Liu(Fudan University), Jiyun Yang(Sichuan Academy of Medical Sciences & Sichuan Provincial People's Hospital), Dongyu Li(Wuhan Puai Hospital), Yi Shi(Sichuan Academy of Medical Sciences & Sichuan Provincial People's Hospital), Yong Tao(University of Electronic Science and Technology of China), Yanhui Deng(University of Electronic Science and Technology of China), Ping Shuai(University of Electronic Science and Technology of China)
Cited by 7
Related Papers
HDL-scavenger receptor B type 1 facilitates SARS-CoV-2 entry
|Nature Metabolism|2020|304
Global, regional, and national burden of chronic kidney disease and its underlying etiologies from 1990 to 2021: a systematic analysis for the Global Burden of Disease Study 2021
|BMC Public Health|2025|148
A common variant mapping to CACNA1A is associated with susceptibility to exfoliation syndrome
|Nature Genetics|2015|129
Genetic factors define CPO and CLO subtypes of nonsyndromicorofacial cleft
|PLoS Genetics|2019|113
Detection of serum IgM and IgG for COVID-19 diagnosis
|Science China Life Sciences|2020|107