Briganti Giovanni, Le Moine Olivier
Medical Informatics, School of Medicine, Université Libre de Bruxelles, Brussels, Belgium.
Unit of Epidemiology, Biostatistics and Clinical Research, School of Public Health, Université Libre de Bruxelles, Brussels, Belgium.
Front Med (Lausanne). 2020 Feb 5;7:27. doi: 10.3389/fmed.2020.00027. eCollection 2020.
Artificial intelligence-powered medical technologies are rapidly evolving into applicable solutions for clinical practice. Deep learning algorithms can deal with increasing amounts of data provided by wearables, smartphones, and other mobile monitoring sensors in different areas of medicine. Currently, only very specific settings in clinical practice benefit from the application of artificial intelligence, such as the detection of atrial fibrillation, epilepsy seizures, and hypoglycemia, or the diagnosis of disease based on histopathological examination or medical imaging. The implementation of augmented medicine is long-awaited by patients because it allows for a greater autonomy and a more personalized treatment, however, it is met with resistance from physicians which were not prepared for such an evolution of clinical practice. This phenomenon also creates the need to validate these modern tools with traditional clinical trials, debate the educational upgrade of the medical curriculum in light of digital medicine as well as ethical consideration of the ongoing connected monitoring. The aim of this paper is to discuss recent scientific literature and provide a perspective on the benefits, future opportunities and risks of established artificial intelligence applications in clinical practice on physicians, healthcare institutions, medical education, and bioethics.
人工智能驱动的医疗技术正在迅速发展成为临床实践的适用解决方案。深度学习算法可以处理可穿戴设备、智能手机和其他移动监测传感器在医学不同领域提供的越来越多的数据。目前,临床实践中只有非常特定的场景受益于人工智能的应用,比如心房颤动、癫痫发作和低血糖的检测,或者基于组织病理学检查或医学成像的疾病诊断。增强医学的实施是患者长期期待的,因为它能带来更大的自主性和更个性化的治疗,然而,它却遭到了医生的抵制,因为他们对临床实践的这种演变毫无准备。这种现象也使得有必要通过传统临床试验来验证这些现代工具,根据数字医学对医学课程的教育升级进行辩论,并对正在进行的连接监测进行伦理考量。本文的目的是讨论最近的科学文献,并就临床实践中已确立的人工智能应用在医生、医疗机构、医学教育和生物伦理方面的益处、未来机遇和风险提供一个观点。