A model-based validation study of postoperative complications with considerations on operative timing.

ABSTRACT:

Background

Surgery is a highly technical procedure relying on high mental acuity and manual dexterity. The possibility that surgical outcomes and post-operative complications could be subject to influence by fatigue and/or circadian rhythms in surgeons has been investigated with inconsistent results.

Methods

We conducted a retrospective study to assess the significance of operative timing on classifying surgical complications using an interpretable machine learning approach. We trained various linear, generative as well as tree models on the surgical record data collected from a university-affiliated, tertiary teaching hospital in China by performing parameter tuning using grid search cross-validation for optimizing the F1 score.

Results

The results indicated that XGB

SUBMITTER: Qian K 

PROVIDER: S-EPMC8106084 | biostudies-literature | 2021 Apr

REPOSITORIES: biostudies-literature