Artificial Intelligence and Acute Appendicitis: A Systematic Review of Diagnostic and Prognostic Models.

ABSTRACT:

Background

To assess the efficacy of artificial intelligence (AI) models in diagnosing and prognosticating acute appendicitis (AA) in adult patients compared to traditional methods. AA is a common cause of emergency department visits and abdominal surgeries. It is typically diagnosed through clinical assessments, laboratory tests, and imaging studies. However, traditional diagnostic methods can be time-consuming and inaccurate. Machine learning models have shown promise in improving diagnostic accuracy and predicting outcomes.

Main body

A systematic review following the PRISMA guidelines was conducted, searching PubMed, Embase, Scopus, and Web of Science databases. Studies were evaluated for risk of bias using the Prediction Model Risk of Bias Assessment Tool. Data points ex

SUBMITTER: Issaiy M 

PROVIDER: S-EPMC10729387 | biostudies-literature | 2023 Dec

REPOSITORIES: biostudies-literature