Weakly Semi-supervised phenotyping using Electronic Health records.

ABSTRACT:

Objective

Electronic Health Record (EHR) based phenotyping is a crucial yet challenging problem in the biomedical field. Though clinicians typically determine patient-level diagnoses via manual chart review, the sheer volume and heterogeneity of EHR data renders such tasks challenging, time-consuming, and prohibitively expensive, thus leading to a scarcity of clinical annotations in EHRs. Weakly supervised learning algorithms have been successfully applied to various EHR phenotyping problems, due to their ability to leverage information from large quantities of unlabeled samples to better inform predictions based on a far smaller number of patients. However, most weakly supervised methods are subject to the challenge to choose the right cutoff value to generate an optimal classifie

SUBMITTER: Nogues IE 

PROVIDER: S-EPMC10112494 | biostudies-literature | 2022 Oct

REPOSITORIES: biostudies-literature