The impact of artificial intelligence in general surgery: enhancing precision, efficiency, and outcomes

Abstract

The integration of artificial intelligence (AI) into general surgery has brought significant advancements in surgical precision, postoperative complication prediction, and intraoperative assistance. Despite its potential, AI faces challenges regarding its broad implementation in clinical practice. This systematic review aims to assess the impact of AI on clinical outcomes in general surgery, including diagnostic accuracy, complication prediction, and surgical error reduction. A systematic review was conducted using PubMed, Scopus, and Web of Science databases, focusing on studies published between 2020 and 2024. Inclusion criteria required studies that evaluated AI’s role in general surgery with a sample size of at least 50 patients. Studies reporting both qualitative and quantitative outcomes, including complication prediction and intraoperative assistance, were included. Ten studies were selected, involving a total of 12,580 patients undergoing various surgical procedures such as hepatectomies, colectomies, and cholecystectomies. AI significantly improved complication prediction accuracy (25% improvement over traditional methods) and reduced intraoperative errors by 18%. Additionally, AI-assisted surgeries showed an average reduction of 30 minutes in surgical time, from 150 to 120 minutes in complex cases. AI has proven to be a valuable tool in general surgery, particularly in complex procedures where precision and complication prediction are critical. However, further studies are needed to validate AI models across diverse populations and healthcare settings to ensure widespread adoption.

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