工作流程
医学
自动化
机器人学
人工智能
航空
医疗保健
风险分析(工程)
数据科学
心理学
计算机科学
机器人
政治学
机械工程
工程类
航空航天工程
数据库
法学
作者
Sandip S. Panesar,Michel Kliot,Rob Parrish,Juan C. Fernandez‐Miranda,Yvonne Cagle,Gavin W. Britz
出处
期刊:Neurosurgery
[Oxford University Press]
日期:2019-11-01
卷期号:87 (1): 33-44
被引量:63
标识
DOI:10.1093/neuros/nyz471
摘要
Abstract Artificial intelligence (AI)-facilitated clinical automation is expected to become increasingly prevalent in the near future. AI techniques may permit rapid and detailed analysis of the large quantities of clinical data generated in modern healthcare settings, at a level that is otherwise impossible by humans. Subsequently, AI may enhance clinical practice by pushing the limits of diagnostics, clinical decision making, and prognostication. Moreover, if combined with surgical robotics and other surgical adjuncts such as image guidance, AI may find its way into the operating room and permit more accurate interventions, with fewer errors. Despite the considerable hype surrounding the impending medical AI revolution, little has been written about potential downsides to increasing clinical automation. These may include both direct and indirect consequences. Directly, faulty, inadequately trained, or poorly understood algorithms may produce erroneous results, which may have wide-scale impact. Indirectly, increasing use of automation may exacerbate de-skilling of human physicians due to over-reliance, poor understanding, overconfidence, and lack of necessary vigilance of an automated clinical workflow. Many of these negative phenomena have already been witnessed in other industries that have already undergone, or are undergoing “automation revolutions,” namely commercial aviation and the automotive industry. This narrative review explores the potential benefits and consequences of the anticipated medical AI revolution from a neurosurgical perspective.
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