Open AccessCharacterizing phenotypic abnormalities associated with high-risk individuals developing lung cancer using electronic health records from the All of Us researcher workbench
Author(s) -
Jie Na,
Nansu Zong,
Chen Wang,
David E. Midthun,
Yuan Luo,
Ping Yang,
Guoqian Jiang
Publication year - 2021
Publication title -
journal of the american medical informatics association
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.614
H-Index - 150
eISSN - 1527-974X
pISSN - 1067-5027
DOI - 10.1093/jamia/ocab174
Subject(s) - medicine , lung cancer , population , cohort , phenome , odds ratio , bonferroni correction , logistic regression , cohort study , risk assessment , gerontology , environmental health , biology , genetics , phenotype , computer science , statistics , mathematics , computer security , gene
The study sought to test the feasibility of conducting a phenome-wide association study to characterize phenotypic abnormalities associated with individuals at high risk for lung cancer using electronic health records.