A correlation-based feature analysis of physical examination indicators can help predict the overall underlying health status using machine learning.

ABSTRACT: As a systematic investigation of the correlations between physical examination indicators (PEIs) is lacking, most PEIs are currently independently used for disease warning. This results in the general physical examination having limited diagnostic values. Here, we systematically analyzed the correlations in 221 PEIs between healthy and 34 unhealthy statuses in 803,614 individuals in China. Specifically, the study population included 711,928 healthy participants, 51,341 patients with hypertension, 12,878 patients with diabetes, and 34,997 patients with other unhealthy statuses. We found rich relevance between PEIs in the healthy physical status (7662 significant correlations, 31.5%). However, in the disease conditions, the PEI correlations changed. We focused on the difference in PEIs betwe

SUBMITTER: Wang H 

PROVIDER: S-EPMC9666446 | biostudies-literature | 2022 Nov

REPOSITORIES: biostudies-literature