Development and Validation of a Machine Learning Model for Early Detection of Untreated Infection.

ABSTRACT:

Background

Early diagnostic uncertainty for infection causes delays in antibiotic administration in infected patients and unnecessary antibiotic administration in noninfected patients.

Objective

To develop a machine learning model for the early detection of untreated infection (eDENTIFI), with the presence of infection determined by clinician chart review.

Derivation cohort

Three thousand three hundred fifty-seven adult patients hospitalized between 2006 and 2018 at two health systems in Illinois, United States.

Validation cohort

We validated in 1632 patients in a third Illinois health system using area under the receiver operating characteristic curve (AUC).

Prediction model

Using a longitudinal discrete-time format, we trained a gradient boosted machin

SUBMITTER: Buell KG 

PROVIDER: S-EPMC11473064 | biostudies-literature | 2024 Oct

REPOSITORIES: biostudies-literature