Artificial Intelligence in Surgery: The Future is Now.

IF 1.7 4区 医学 Q2 SURGERY
Ahmad Guni, Piyush Varma, Joe Zhang, Matyas Fehervari, Hutan Ashrafian
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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.

人工智能在外科手术中的应用:未来就在眼前。
背景 临床人工智能(AI)已经到了一个关键的拐点。算法科学的进步以及对人工智能部署中的操作考虑因素的进一步了解,正在为广泛的临床路径变革打开大门。特别是对于外科手术而言,计算机视觉和手术机器人等领域的机器学习算法的应用将从根本上改变我们在术前、术后和手术室内筛查、诊断、风险分级、治疗和随访病人的方式。摘要 在本文中,我们总结了复杂手术护理路径中现有和新兴集成的现状。我们研究了在整个患者治疗过程中实际使用人工智能的有效方法,从早期筛查和准确诊断到术中机器人技术、术后监测和随访。对人工智能技术在外科手术中的应用进行地平线扫描,以确定可提高当今外科手术实践水平的新型创新技术,并为未来外科手术实践核心领域的范式转变提供可能。任何人工智能驱动的未来都必须建立在负责任和合乎道德的使用基础上,并通过有效监督数据管理和部署中的患者安全风险来加强。此外,实施过程中还必须考虑可用性和路径可行性,以及对医疗保健技术评估和证据生成的需求。虽然这些因素在传统上被视为将人工智能转化为实践的障碍,但我们将讨论如何通过全面的实施实践为在整个路径中推广人工智能奠定坚实的基础。关键信息 未来十年,实验发展将迅速转化为对现实世界的影响。人工智能将要求工作实践的演变,但同时也将加强患者安全、提高手术质量结果,并为外科医生和医疗系统带来巨大价值。外科手术一直以来都是以技术创新为基础的。对于那些遵循这一传统的人来说,人工智能在外科领域的未来从现在开始。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
2.30
自引率
6.20%
发文量
31
审稿时长
>12 weeks
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.
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