Innovative Applications and Challenges of Artificial Intelligence in Surgical Oncology

This paper reviews the latest advances in the application of Artificial Intelligence (AI) technologies in the domain of surgical oncology, and the challenges they face. The application of AI in surgical oncology encompasses a wide range of medical image analysis, preoperative planning and simulation, surgical navigation and robotic-assisted surgery, as well as postoperative monitoring and follow-up. The utilisation of computer-aided diagnosis (CAD) systems, deep learning models (e.g., U-Net), three-dimensional reconstruction techniques, and virtual reality (VR) has led to a substantial enhancement in the accuracy of tumour detection, the precision of surgical planning, and the safety of surgical operations. Concurrently, the integration of AI with postoperative data analysis and prediction models furnishes patients with personalised recovery plans and an enhanced prognosis. However, the application of AI in surgical oncology still faces challenges such as data privacy and security, algorithm performance validation, and multidisciplinary cooperation. In the future, with the continuous optimisation of the technology and the integration of multimodal data, AI is expected to drive oncology treatment in the direction of greater precision and personalisation, bringing about a revolutionary change in oncology surgery.