Challenges and opportunities for artificial intelligence in surgery

IF 1 Q3 ENGINEERING, MULTIDISCIPLINARY
P. Andreatta, Christopher S. Smith, J. Graybill, M. Bowyer, E. Elster
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引用次数: 0

Abstract

Surgery is an exceptionally complex domain where multi-dimensional expertise is developed over an extended period of time, and mastery is maintained only through ongoing engagement in surgical contexts. Expert surgeons integrate perceptual information through both conscious and subconscious awareness, and respond to the environment by leveraging their deep understanding of surgical constructs. However, their ability to utilize these deep knowledge structures can be complicated by continuous advances in technology, medical science, pharmacology, technique, materials, operative environments, etc. that must be routinely accommodated in professional practice. The demands on surgeons to perform perfectly in ever-changing contexts increases cognitive load, which could be reduced through judicious use of accurate and reliable artificial intelligence (AI) systems. AI has great potential to support human performance in complex environments such as surgery; however, the foundational requirements for the rules governing algorithmic development of performance requirements necessitate the active involvement of surgeons to precisely model the quantitative measures of performance along the continuum of expertise. Providing the AI development community with these data will help assure that accurate and reliable systems are designed to supplement human performance in applied surgical contexts. The Military Health System’s Clinical Readiness Program is developing these types of metrics to support military medical readiness.
人工智能在外科手术中的挑战与机遇
外科是一个异常复杂的领域,需要在很长一段时间内发展出多维度的专业知识,只有通过持续参与外科环境才能保持精通。专家外科医生通过有意识和潜意识的意识整合感知信息,并利用他们对手术结构的深刻理解来对环境做出反应。然而,他们利用这些深层知识结构的能力可能会因为技术、医学、药理学、技术、材料、手术环境等方面的不断进步而变得复杂,这些都必须在专业实践中常规适应。对外科医生在不断变化的环境中完美表现的要求增加了认知负荷,这可以通过明智地使用准确可靠的人工智能(AI)系统来减少。人工智能在支持人类在手术等复杂环境中的表现方面具有巨大潜力;然而,管理性能要求的算法开发规则的基本要求需要外科医生积极参与,沿着专业知识的连续体精确地模拟性能的定量测量。向人工智能开发社区提供这些数据将有助于确保设计准确可靠的系统,以补充应用外科环境中的人类表现。军事卫生系统的临床准备计划正在开发这些类型的指标来支持军事医疗准备。
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
2.80
自引率
12.50%
发文量
40
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