A Systematic Integration of Artificial Intelligence Models in Appendicitis Management: A Comprehensive Review

Area of Science:

• Medical Informatics
• Artificial Intelligence in Medicine
• Surgical Innovation

Background:

• Acute appendicitis management relies on timely diagnosis and effective treatment.
• Current diagnostic and treatment pathways face challenges in accuracy and efficiency.
• The integration of artificial intelligence (AI) and machine learning (ML) offers potential solutions.

Purpose of the Study:

• To comprehensively review AI and ML applications across the entire spectrum of acute appendicitis care.
• To assess the impact of AI on diagnostic accuracy, treatment optimization, and patient outcomes.
• To identify current challenges and future directions for AI in appendicitis management.

Main Methods:

• Systematic literature search across major scientific databases (PubMed/MEDLINE, IEEE Xplore, arXiv, Web of Science, Scopus) up to February 14, 2025.
• Review of AI/ML applications in triage, diagnosis, severity prediction, intraoperative assistance, and postoperative management of appendicitis.
• Analysis of studies evaluating AI model performance, clinical utility, and integration challenges.

Main Results:

• AI demonstrates potential in rapid triage and accurate diagnosis of appendicitis using diverse data.
• ML algorithms improve diagnostic accuracy, predict disease severity, and guide treatment decisions.
• Emerging AI tools assist in intraoperative procedures and predict postoperative complications like abscess and sepsis.
• Radiomics enhances diagnostic precision through advanced imaging data analysis.

Conclusions:

• AI and ML are transforming acute appendicitis care, offering enhanced diagnostic capabilities and personalized treatment strategies.
• Despite significant potential, challenges in data quality, interpretability, ethics, and clinical integration need to be addressed.
• Future research should focus on developing integrated AI-assisted workflows to optimize patient outcomes and ensure equitable access.