Ahmad Guni, Piyush Varma, Joe Zhang, Matyas Fehervari, Hutan Ashrafian
{"title":"Artificial Intelligence in Surgery: The Future is Now.","authors":"Ahmad Guni, Piyush Varma, Joe Zhang, Matyas Fehervari, Hutan Ashrafian","doi":"10.1159/000536393","DOIUrl":null,"url":null,"abstract":"<p><p>Background Clinical Artificial intelligence (AI) has reached a critical inflection point. Advances in algorithmic science and increased understanding of operational considerations in AI deployment are opening the door to widespread clinical pathway transformation. For surgery in particular, the application of machine learning algorithms in fields such as computer vision and operative robotics are poised to radically change how we screen, diagnose, risk-stratify, treat and follow-up patients, in both pre- and post-operative stages, and within operating theatres. Summary In this paper, we summarise the current landscape of existing and emerging integrations within complex surgical care pathways. We investigate effective methods for practical use of AI throughout the patient pathway, from early screening and accurate diagnosis to intraoperative robotics, post-operative monitoring and follow-up. Horizon scanning of AI technologies in surgery is used to identify novel innovations that can enhance surgical practice today, with potential for paradigm shifts across core domains of surgical practice in the future. Any AI-driven future must be built on responsible and ethical usage, reinforced by effective oversight of data governance, and of risks to patient safety in deployment. Implementation is additionally bound to considerations of usability and pathway feasibility, and the need for robust healthcare technology assessment and evidence generation. While these factors are traditionally seen as barriers to translating AI into practice, we discuss how holistic implementation practices can create a solid foundation for scaling AI across pathways. Key Messages The next decade will see rapid translation of experimental development into real-world impact. AI will require evolution of work practices, but will also enhance patient safety, enhance surgical quality outcomes, and provide significant value for surgeons and health systems. Surgical practice has always sat on a bedrock of technological innovation. For those that follow this tradition, the future of AI in surgery starts now.</p>","PeriodicalId":12222,"journal":{"name":"European Surgical Research","volume":" ","pages":""},"PeriodicalIF":1.7000,"publicationDate":"2024-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"European Surgical Research","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1159/000536393","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"SURGERY","Score":null,"Total":0}
引用次数: 0
Abstract
Background Clinical Artificial intelligence (AI) has reached a critical inflection point. Advances in algorithmic science and increased understanding of operational considerations in AI deployment are opening the door to widespread clinical pathway transformation. For surgery in particular, the application of machine learning algorithms in fields such as computer vision and operative robotics are poised to radically change how we screen, diagnose, risk-stratify, treat and follow-up patients, in both pre- and post-operative stages, and within operating theatres. Summary In this paper, we summarise the current landscape of existing and emerging integrations within complex surgical care pathways. We investigate effective methods for practical use of AI throughout the patient pathway, from early screening and accurate diagnosis to intraoperative robotics, post-operative monitoring and follow-up. Horizon scanning of AI technologies in surgery is used to identify novel innovations that can enhance surgical practice today, with potential for paradigm shifts across core domains of surgical practice in the future. Any AI-driven future must be built on responsible and ethical usage, reinforced by effective oversight of data governance, and of risks to patient safety in deployment. Implementation is additionally bound to considerations of usability and pathway feasibility, and the need for robust healthcare technology assessment and evidence generation. While these factors are traditionally seen as barriers to translating AI into practice, we discuss how holistic implementation practices can create a solid foundation for scaling AI across pathways. Key Messages The next decade will see rapid translation of experimental development into real-world impact. AI will require evolution of work practices, but will also enhance patient safety, enhance surgical quality outcomes, and provide significant value for surgeons and health systems. Surgical practice has always sat on a bedrock of technological innovation. For those that follow this tradition, the future of AI in surgery starts now.
期刊介绍:
''European Surgical Research'' features original clinical and experimental papers, condensed reviews of new knowledge relevant to surgical research, and short technical notes serving the information needs of investigators in various fields of operative medicine. Coverage includes surgery, surgical pathophysiology, drug usage, and new surgical techniques. Special consideration is given to information on the use of animal models, physiological and biological methods as well as biophysical measuring and recording systems. The journal is of particular value for workers interested in pathophysiologic concepts, new techniques and in how these can be introduced into clinical work or applied when critical decisions are made concerning the use of new procedures or drugs.