Prognostic machine learning models for predicting postoperative complications following general surgery in Bandar Abbas, Iran: a study protocol.

ABSTRACT:

Introduction

To enhance the quality of surgical care, complications need to be minimised. Consequently, comprehending the occurrence and risk elements for postoperative complications is essential. Subsequently, we will apply machine learning (ML) algorithms to build risk factor prediction models that will assist surgeons in identifying the risk factors associated with the development of postoperative complications after general surgery.

Methods and analysis

This research will take place at a tertiary referral medical centre located in Bandar Abbas, Hormozgan, Iran. The inclusion criteria are (1) individuals aged 18 years or older who have any type of general surgery and (2) hospitalised from September 2025 to September 2026. Individuals with insufficient data will be exclude

SUBMITTER: Vatankhah Tarbebar M 

PROVIDER: S-EPMC12570904 | biostudies-literature | 2025 Oct

REPOSITORIES: biostudies-literature