Application of artificial intelligence in surgery
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REVIEW
Application of artificial intelligence in surgery Xiao-Yun Zhou (
✉)1, Yao Guo1, Mali Shen1, Guang-Zhong Yang2
1
The Hamlyn Centre for Robotic Surgery, Imperial College London, London SW7 2AZ, UK; 2Institute of Medical Robotics, Shanghai Jiao Tong University, Shanghai 200240, China
© Higher Education Press 2020
Abstract Artificial intelligence (AI) is gradually changing the practice of surgery with technological advancements in imaging, navigation, and robotic intervention. In this article, we review the recent successful and influential applications of AI in surgery from preoperative planning and intraoperative guidance to its integration into surgical robots. We conclude this review by summarizing the current state, emerging trends, and major challenges in the future development of AI in surgery. Keywords
artificial intelligence; surgical autonomy; medical robotics; deep learning
Introduction Advances in surgery have revolutionized the management of both acute and chronic diseases, prolonging life and extending the boundary of patient survival. These advances are underpinned by continuing technological developments in diagnosis, imaging, and surgical instrumentation. Complex surgical navigation and planning are made possible through the use of both pre- and intraoperative imaging techniques, such as ultrasound, computed tomography (CT), and magnetic resonance imaging (MRI) [1]. Surgical trauma is reduced through minimally invasive surgery (MIS), which is now progressively combined with robotic assistance [2]. Postoperative care is also improved by sophisticated wearable and implantable sensors for supporting early discharge after surgery, thereby enhancing patient recovery and early detection of postsurgical complications [3,4]. Numerous terminal illnesses have been transformed into clinically manageable chronic lifelong conditions, and surgery is increasingly focused on the systematic effects of this procedure on patients, avoiding isolated surgical treatment or anatomical alteration, with careful consideration of metabolic, hemodynamic, and neurohormonal consequences that can influence the quality of life. Owing to recent advances in medicine, artificial intelligence (AI) has played an important role in supporting clinical decision-making since the early years of the Received August 19, 2019; accepted March 5, 2020 Correspondence: Xiao-Yun Zhou, [email protected]
development of the MYCIN system [5]. AI is now increasingly used for risk stratification, genomics, imaging and diagnosis, precision medicine, and drug discovery. AI was introduced into surgery more recently, with a strong root in imaging and navigation and early techniques focusing on feature detection and computer-assisted intervention for both preoperative planning and intraoperative guidance. Over the years, supervised algorithms, such as active-shape models, atlas-based methods, and statistical classifiers, have been developed [1]. The recent successes of deep convolutional neural network (DCNN), such as AlexNet [6], have enabl
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