Predictive effect of postoperative recovery in general anesthesia patients using interpretable models based on swarm intelligence machine learning.

ABSTRACT:

Objective

To analyze the clinical value of predicting postoperative recovery in patients undergoing general anesthesia using an interpretable model based on swarm intelligence machine learning.

Methods

This study retrospectively collected data from 1,128 patients who underwent general anesthesia at Sir Run Run Shaw Hospital, affiliated with Zhejiang University School of Medicine, from January 2021 to January 2024. Based on predefined inclusion and exclusion criteria, a total of 1,128 patients were included in the study, comprising Dataset A. Additionally, patients meeting the same criteria from Sir Run Run Shaw Hospital Affiliated to Zhejiang University School of Medicine Alar Hospital during the period January 2021 - January 2024 were selected, constituting Dataset B. Datas

SUBMITTER: Hua C 

PROVIDER: S-EPMC12426152 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature