Artificial Intelligence in Surgical Research: Transformative Impacts and Evolving Ethical Challenges

Abstract

Artificial intelligence (AI) has rapidly emerged as a transformative force in surgical research, driving innovation in preoperative planning, intraoperative guidance, workflow optimization, and academic productivity. Advances in computational power and multimodal data have expanded applications beyond retrospective analytics and predictive modeling to real-time clinical decision support. Current use cases span AI-assisted three-dimensional planning, automated scheduling, and ambient scribe technology. Simultaneously, large language models are increasingly applied to literature synthesis, data analysis, and manuscript development. Yet, this rapid integration raises critical ethical concerns, including algorithmic bias, data privacy, model opacity, and issues of accountability and generalizability. This review synthesizes recent technological advancements and examines these ethical challenges, proposing structured frameworks for responsible implementation. By embedding principles of transparency, equity, and patient safety, the surgical research community can ensure AI innovation translates into meaningful and trustworthy improvements in care.

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