Identifying infected patients using semi-supervised and transfer learning.

ABSTRACT:

Objectives

Early identification of infection improves outcomes, but developing models for early identification requires determining infection status with manual chart review, limiting sample size. Therefore, we aimed to compare semi-supervised and transfer learning algorithms with algorithms based solely on manual chart review for identifying infection in hospitalized patients.

Materials and methods

This multicenter retrospective study of admissions to 6 hospitals included "gold-standard" labels of infection from manual chart review and "silver-standard" labels from nonchart-reviewed patients using the Sepsis-3 infection criteria based on antibiotic and culture orders. "Gold-standard" labeled admissions were randomly allocated to training (70%) and testing (30%) datasets. Us

SUBMITTER: Bashiri FS 

PROVIDER: S-EPMC9471712 | biostudies-literature | 2022 Sep

REPOSITORIES: biostudies-literature