Artificial intelligence algorithms permits rapid acute kidney injury risk classification of patients with acute myocardial infarction.

ABSTRACT:

Objective

This study aimed to develop and validate several artificial intelligence (AI) models to identify acute myocardial infarction (AMI) patients at an increased risk of acute kidney injury (AKI) during hospitalization.

Methods

Included were patients diagnosed with AMI from the Medical Information Mart for Intensive Care (MIMIC) III and IV databases. Two cohorts of AMI patients from Changzhou Second People's Hospital and Xuzhou Center Hospital were used for external validation of the models. Patients' demographics, vital signs, clinical characteristics, laboratory results, and therapeutic measures were extracted. Totally, 12 AI models were developed. The area under the receiver operating characteristic curve (AUC) were calculated and compared.

Results

AKI occurred

SUBMITTER: Wei J 

PROVIDER: S-EPMC11367145 | biostudies-literature | 2024 Aug

REPOSITORIES: biostudies-literature