Use of Machine Learning to Develop and Evaluate Models Using Preoperative and Intraoperative Data to Identify Risks of Postoperative Complications.

ABSTRACT:

Importance

Postoperative complications can significantly impact perioperative care management and planning.

Objectives

To assess machine learning (ML) models for predicting postoperative complications using independent and combined preoperative and intraoperative data and their clinically meaningful model-agnostic interpretations.

Design, setting, and participants

This retrospective cohort study assessed 111 888 operations performed on adults at a single academic medical center from June 1, 2012, to August 31, 2016, with a mean duration of follow-up based on the length of postoperative hospital stay less than 7 days. Data analysis was performed from February 1 to September 31, 2020.

Main outcomes and measures

Outcomes included 5 postoperative complications: acu

SUBMITTER: Xue B 

PROVIDER: S-EPMC8010590 | biostudies-literature | 2021 Mar

REPOSITORIES: biostudies-literature