Performance of artificial intelligence models for predicting intraoperative complications during surgery in real time: a systematic review and meta-analysis protocol.

ABSTRACT:

Introduction

Intraoperative complications contribute significantly to morbidity and mortality, and reducing their risk is a primary objective for all operating room's healthcare professionals. Many of these complications are predictable and could be anticipated by the surgeon or anaesthesiologist. Various clinical scores were developed to assess cardiovascular risk, acute kidney injury or acute respiratory failure preoperatively. However, these scores require time for calculation and are not designed to be adjusted in real time during surgery, based on physiological signals and new intraoperative events. Besides, some events remain unpredictable because they are multifactorial.In recent decades, Artificial Intelligence (AI)-based algorithms have been tested for the real-time predic

SUBMITTER: Bronnert R 

PROVIDER: S-EPMC12542564 | biostudies-literature | 2025 Oct

REPOSITORIES: biostudies-literature