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Review
. 2025 Jun;32(3):301-311.
doi: 10.1177/15533506251328481. Epub 2025 Mar 19.

The Role of AI in Modern Hernia Surgery: A Review and Practical Insights

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Review

The Role of AI in Modern Hernia Surgery: A Review and Practical Insights

Gabriela Restrepo-Rodas et al. Surg Innov. 2025 Jun.

Abstract

BackgroundArtificial intelligence (AI) is revolutionizing various aspects of health care, particularly in the surgical field, where it offers significant potential for improving surgical risk assessment, predictive analytics, and research advancement. Despite the development of numerous AI models in surgery, there remains a notable gap in understanding their specific application within the context of hernia surgery.PurposeThis review aims to explore the evolution of AI utilization in hernia surgery over the past 2 decades, focusing on the contributions of Machine Learning (ML), Natural Language Processing (NLP), Computer Vision (CV), and Robotics.ResultsWe discuss how these AI fields enhance surgical outcomes and advance research in the domain of hernia surgery. ML focuses on developing and training prediction models, while NLP enables seamless human-computer interaction through the use of Large Language Models (LLMs). CV assists in critical view detection, which is crucial in procedures such as inguinal hernia repair, and robotics improves minimally invasive techniques, dexterity, and precision. We examine recent evidence and the applicability of various AI models on hernia patients, considering the strengths, limitations, and future possibilities within each field.ConclusionBy consolidating the impact of AI models on hernia surgery, this review provides insights into the potential of AI for advancing patient care and surgical techniques in this field, ultimately contributing to the ongoing evolution of surgical practice.

Keywords: artificial intelligence; computer vision; hernia surgery; machine learning; surgical robotics.

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Conflict of interest statement

Declaration of Conflicting InterestsThe author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

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