Systematic review highlights AI's role in predicting postoperative complications in abdominal wall reconstruction, suggesting potential improvements for surgical outcomes.
Aim: The use of artificial intelligence (AI) in medicine has grown significantly in recent years. This systematic review aims to highlight current trends in the application of AI specifically in abdominal wall reconstruction, which represents one of many medical fields utilizing AI technology. Methods: A systematic review was conducted following the preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines. Electronic databases including PubMed, Google Scholar, EBSCO, Ovid, and the Cochrane Library were searched for studies published between 2000 and 2024 that evaluated AI applications in abdominal wall reconstruction. Results: A total of 142 publications were identified, of which 12 met the inclusion criteria and were included in this review. All included studies were published between 2019 and 2024. Among these, 2 studies investigated AI models for predicting hernia occurrence and the need for abdominal wall reconstruction; 1 study focused on AI for preoperative planning; 6 articles examined AI-based prediction of postoperative complications; and 3 publications explored the use of AI to answer patient questions. Conclusion: Current research on AI in abdominal wall reconstruction primarily focuses on predicting postoperative outcomes and minimizing complications. However, there is no established consensus regarding the optimal applications or methodologies for integrating AI in this surgical field.
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Liu et al. (2025) studied this question.
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