REVIEW   

Minerva Surgery 2024 Mar 13

DOI: 10.23736/S2724-5691.23.10156-0

Copyright © 2023 EDIZIONI MINERVA MEDICA

language: English

Current use of artificial intelligence in the diagnosis and management of acute appendicitis

Micaela CAPPUCCIO ¹, Paolo BIANCO ², Marco ROTONDO ³, Salvatore SPIEZIA ³, Marco D’AMBROSIO ³, Francesco MENEGON TASSELLI ⁴, Germano GUERRA ³, Pasquale AVELLA ^{1, 2} ✉

¹ Department of Clinical Medicine and Surgery, University of Naples Federico II, Naples, Italy; ² Hepatobiliary and Pancreatic Surgery Unit, Pineta Grande Hospital, Castel Volturno, Caserta, Italy; ³ V. Tiberio Department of Medicine and Health Sciences, University of Molise, Campobasso, Italy; ⁴ General Surgery Unit, A. Cardarelli Hospital, Campobasso, Italy

INTRODUCTION: Acute appendicitis is a common and time-sensitive surgical emergency, requiring rapid and accurate diagnosis and management to prevent complications. Artificial intelligence (AI) has emerged as a transformative tool in healthcare, offering significant potential to improve the diagnosis and management of acute appendicitis. This review provides an overview of the evolving role of AI in the diagnosis and management of acute appendicitis, highlighting its benefits, challenges, and future perspectives.
EVIDENCE ACQUISITION: We performed a literature search on articles published from 2018 to September 2023. We included only original articles.
EVIDENCE SYNTHESIS: Overall, 121 studies were examined. We included 32 studies: 23 studies addressed the diagnosis, five the differentiation between complicated and uncomplicated appendicitis, and 4 studies the management of acute appendicitis.
CONCLUSIONS: AI is poised to revolutionize the diagnosis and management of acute appendicitis by improving accuracy, speed and consistency. It could potentially reduce healthcare costs. As AI technologies continue to evolve, further research and collaboration are needed to fully realize their potential in the diagnosis and management of acute appendicitis.

KEY WORDS: Artificial intelligence; Appendicitis; Diagnosis; Radiomics; Machine learning