Explainable artificial intelligence: enhancing decision-making in plastic surgery

Abstract

Artificial intelligence (AI) models increasingly influence plastic surgery practice through risk prediction, outcome forecasting, and treatment planning. However, their "black box" nature often prevents surgeons from understanding the reasoning behind AI-generated recommendations, limiting clinical adoption and trust. This manuscript presents Explainable Artificial Intelligence (XAI) approaches that can transform opaque AI systems into transparent decision support tools for plastic surgeons. We outline methods for individual case explanations, population-level insights, and visualization techniques specifically relevant to plastic surgery applications. By integrating XAI into clinical workflows, surgeons can leverage AI's predictive power while maintaining their critical role in patient-centered decision-making, ultimately enhancing both the art and science of plastic surgery.