Risk-Specific Training Cohorts to Address Class Imbalance in Surgical Risk Prediction.

ABSTRACT:

Importance

Machine learning tools are increasingly deployed for risk prediction and clinical decision support in surgery. Class imbalance adversely impacts predictive performance, especially for low-incidence complications.

Objective

To evaluate risk-prediction model performance when trained on risk-specific cohorts.

Design, setting, and participants

This cross-sectional study performed from February 2024 to July 2024 deployed a deep learning model, which generated risk scores for common postoperative complications. A total of 109 445 inpatient operations performed at 2 University of Florida Health hospitals from June 1, 2014, to May 5, 2021 were examined.

Exposures

The model was trained de novo on separate cohorts for high-risk, medium-risk, and low-risk Commo

SUBMITTER: Balch JA 

PROVIDER: S-EPMC11465118 | biostudies-literature | 2024 Dec

REPOSITORIES: biostudies-literature