Enabling phenotypic big data with PheNorm.
Electronic health record (EHR)-based phenotyping infers whether a patient has a disease based on the information in his or her EHR. A human-annotated training set with gold-standard disease status labels is usually required to build an algorithm for phenotyping based on a set of predictive features. The time intensiveness of annotation and feature curation severely limits the ability to achieve high-throughput phenotyping. While previous studies have successfully automated feature curation [...]
Author(s): Yu, Sheng, Ma, Yumeng, Gronsbell, Jessica, Cai, Tianrun, Ananthakrishnan, Ashwin N, Gainer, Vivian S, Churchill, Susanne E, Szolovits, Peter, Murphy, Shawn N, Kohane, Isaac S, Liao, Katherine P, Cai, Tianxi
DOI: 10.1093/jamia/ocx111