Lindroth Heidi, Nalaie Keivan, Raghu Roshini, Ayala Ivan N, Busch Charles, Bhattacharyya Anirban, Moreno Franco Pablo, Diedrich Daniel A, Pickering Brian W, Herasevich Vitaly
Division of Nursing Research, Department of Nursing, Mayo Clinic, Rochester, MN 55905, USA.
Center for Aging Research, Regenstrief Institute, School of Medicine, Indiana University, Indianapolis, IN 46202, USA.
J Imaging. 2024 Mar 28;10(4):81. doi: 10.3390/jimaging10040081.
Computer vision (CV), a type of artificial intelligence (AI) that uses digital videos or a sequence of images to recognize content, has been used extensively across industries in recent years. However, in the healthcare industry, its applications are limited by factors like privacy, safety, and ethical concerns. Despite this, CV has the potential to improve patient monitoring, and system efficiencies, while reducing workload. In contrast to previous reviews, we focus on the end-user applications of CV. First, we briefly review and categorize CV applications in other industries (job enhancement, surveillance and monitoring, automation, and augmented reality). We then review the developments of CV in the hospital setting, outpatient, and community settings. The recent advances in monitoring delirium, pain and sedation, patient deterioration, mechanical ventilation, mobility, patient safety, surgical applications, quantification of workload in the hospital, and monitoring for patient events outside the hospital are highlighted. To identify opportunities for future applications, we also completed journey mapping at different system levels. Lastly, we discuss the privacy, safety, and ethical considerations associated with CV and outline processes in algorithm development and testing that limit CV expansion in healthcare. This comprehensive review highlights CV applications and ideas for its expanded use in healthcare.
计算机视觉（CV）是一种人工智能（AI），它利用数字视频或一系列图像来识别内容，近年来已在各个行业中广泛应用。然而，在医疗行业，其应用受到隐私、安全和伦理问题等因素的限制。尽管如此，计算机视觉仍有潜力改善患者监测和系统效率，同时减轻工作量。与以往的综述不同，我们关注的是计算机视觉的终端用户应用。首先，我们简要回顾并分类计算机视觉在其他行业的应用（工作增强、监视和监测、自动化以及增强现实）。然后，我们回顾计算机视觉在医院环境、门诊和社区环境中的发展情况。重点介绍了在谵妄、疼痛和镇静、患者病情恶化、机械通气、活动能力、患者安全、手术应用、医院工作量量化以及院外患者事件监测等方面的最新进展。为了确定未来应用的机会，我们还在不同系统层面完成了流程映射。最后，我们讨论了与计算机视觉相关的隐私、安全和伦理考量，并概述了算法开发和测试过程中限制计算机视觉在医疗保健领域扩展的因素。这篇全面的综述突出了计算机视觉在医疗保健领域的应用及其扩展应用的思路。
