Roles of Artificial Intelligence in Soft Tissue Surgery: A Review

Abstract

Artificial intelligence (AI) is gradually transforming surgical approaches in human and veterinary medicine, but its application in soft tissue surgery is still in its early stages. The present study aimed to comprehensively examine the roles of AI in soft-tissue surgery and to outline the prospects for using AI in veterinary medicine based on in vivo studies. A comprehensive search was performed across PubMed, Scopus, Web of Science, and the Cochrane Library for peer-reviewed articles published from January 2020 to January 2026. Subsequently, 17 studies were selected and evaluated. The current findings indicated that deep learning algorithms, especially convolutional neural networks and computer vision-based models, have been successful in different areas. These areas included preoperative and intraoperative image navigation and recording, automatic detection of tissue edges and differentiation of vital structures from damaged tissues, and guidance of surgical robots during delicate cutting and suturing movements. In vivo studies in small animal models (rats and rabbits) have confirmed the high accuracy of AI-based technologies under physiological conditions, yet there remains a significant gap between these technologies and their routine clinical application in veterinary medicine. Main challenges in translating AI systems from experimental in vivo studies to routine clinical application in veterinary medicine included the need for large amounts of labeled data across different animal species, anatomical variation between breeds, the high cost of robotic hardware, and the lack of common evaluation guidelines. The present study indicated that veterinary medicine is moving towards the development and use of real-time decision-support systems, telesurgery, and multimodal data integration.

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