Mature artificial intelligence– and machine learning–enabled medical tools impacting vascular surgical care: A scoping review of late-stage, US Food and Drug Administration–approved or cleared technologies relevant to vascular surgeons

IF 4.3 3区 材料科学 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC
David P. Stonko, Caitlin W. Hicks
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Abstract

Artificial intelligence and machine learning (AI/ML)-enabled tools are shifting from theoretical or research-only applications to mature, clinically useful tools. The goal of this article was to provide a scoping review of the most mature AI/ML-enabled technologies reviewed and cleared by the US Food and Drug Administration relevant to the field of vascular surgery. Despite decades of slow progress, this landscape is now evolving rapidly, with more than 100 AI/ML-powered tools being approved by the US Food and Drug Administration each year. Within the field of vascular surgery specifically, this review identified 17 companies with mature technologies that have at least one US Food and Drug Administration clearance, all occurring between 2016 and 2022. The maturation of these technologies appears to be accelerating, with improving regulatory clarity and clinical uptake. The early AI/ML-powered devices extend or amplify clinically entrenched platform technologies and tend to be focused on the diagnosis or evaluation of time-sensitive, clinically important pathologies (eg, reading Digital Imaging and Communications in Medicine–compliant computed tomography images to identify pulmonary embolism), or when physician efficiency or time savings is improved (eg, preoperative planning and intraoperative guidance). The majority (>75%) of these technologies are at the intersection of radiology and vascular surgery. It is becoming increasingly important that the contemporary vascular surgeon understands this shifting paradigm, as these once-nascent technologies are finally maturing and will be encountered with increasingly regularity in daily clinical practice.

影响血管外科护理的成熟人工智能和机器学习医疗工具:美国食品和药物管理局批准或批准的血管外科医生相关技术的后期范围审查。
人工智能和机器学习(AI/ML)工具正在从仅用于理论或研究的应用转向成熟的、临床有用的工具。本文的目的是对美国食品药品监督管理局审查和批准的与血管外科领域相关的最成熟的AI/ML技术进行范围审查。尽管几十年来进展缓慢,但这一格局现在正在迅速演变,美国食品和药物管理局每年批准100多个人工智能/机器学习工具。特别是在血管外科领域,这项审查确定了17家拥有成熟技术的公司,这些公司至少获得了美国食品药品监督管理局的一项许可,所有这些公司都发生在2016年至2022年之间。随着监管的清晰度和临床应用的提高,这些技术的成熟似乎正在加速。早期的AI/ML驱动设备扩展或放大了临床上根深蒂固的平台技术,并倾向于专注于对时间敏感的、临床上重要的病理学的诊断或评估(例如,读取符合医学数字成像和通信标准的计算机断层扫描图像以识别肺栓塞),或者当医生的效率或时间节约得到改善时(例如术前计划和术中指导)。这些技术中的大多数(>75%)处于放射学和血管外科的交叉点。当代血管外科医生理解这种不断变化的范式变得越来越重要,因为这些曾经新生的技术终于成熟了,并且在日常临床实践中会越来越规律地遇到。
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
7.20
自引率
4.30%
发文量
567
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