Use of Artificial Intelligence in Preoperative Planning in Surgery: A Narrative Review

Abstract

The integration of artificial intelligence (AI) into preoperative planning for surgery has shown significant potential for enhancing surgical outcomes. AI technologies, such as machine learning (ML), deep learning, three-dimensional (3D) modeling, and predictive analytics, are increasingly being used to improve the accuracy of surgical planning, risk stratification, and patient outcomes. The aim of this narrative review was primarily to evaluate the applications, effectiveness, and limitations of AI in preoperative surgical planning. This review synthesized findings from recent studies published between 2020 and 2025, focusing on the use of AI in preoperative planning across surgical specialties, with particular attention to well-documented examples from plastic and reconstructive surgery. AI technologies, including ML algorithms, 3D modeling, and predictive analytics, have shown promise in potentially improving surgical precision, reducing complications, and enhancing patient satisfaction across multiple surgical procedures. However, challenges related to data heterogeneity, publication bias, and the limited number of large-scale prospective multicenter clinical studies remain significant barriers to its broader implementation. AI can potentially support preoperative planning in surgery by augmenting surgical decision-making and contributing to improved clinical outcomes. Integrating AI with emerging technologies, such as 3D printing and virtual reality, could further expand its applications in surgical planning and patient care.

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