人工智能和远程医疗在麻醉学、重症监护和疼痛医学领域的应用

E. Bignami, Michele Russo, Valentina Bellini, P. Berchialla, G. Cammarota, M. Cascella, C. Compagnone, F. Sanfilippo, S. Maggiore, J. Montomoli, L. Vetrugno, E. Boero, A. Cortegiani, A. Giarratano, P. Pelosi, E. De Robertis
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引用次数: 1

摘要

人工智能在改善人类生活和医疗实践方面的潜在作用正在调查中,但医疗保健提供者对这一主题的了解尚不充分。调查麻醉、重症监护和疼痛医学领域的医生对人工智能的了解情况。作为次要结果,我们调查了人工智能实施的主要关注点。在线调查。麻醉学,重症监护和疼痛医学。我们邀请了麻醉、复苏、重症监护和疼痛医学方面的临床医生,他们是欧洲麻醉和重症监护学会(ESAIC)的活跃成员。2022年6月28日至2022年10月29日的在线调查。主要结果是调查参与者的人工智能和远程医疗知识。共发送邮件4465封,专家220人,年龄46.5±10.2岁;128名男性(58.2%)回应了调查。总的来说,220名成员中有207名(94.1%)和180名(81.8%)成员分别对人工智能和机器学习有所了解。在麻醉学领域,220人中有168人(76.4%)和151人(68.6%)听说过人工智能和机器学习。在重症监护室,220人中有154人(70.0%)和133人(60.5%)听说过人工智能和机器学习,而在疼痛医学中,这些数字要低得多[人工智能:只有70/220(31.8%)和机器学习67/220(30.5%)]。在临床实践中实施这些工具的主要障碍是:缺乏导致结果的算法知识;可用的验证研究很少,对人工智能的了解也不够。220名成员中有212名(96.4%)报告了远程医疗知识。大多数麻醉师都知道人工智能和机器学习。对人工智能在麻醉学、重症监护和疼痛管理中的应用的总体看法是积极的,大多数参与者不认为这一工具会对他们的职业构成威胁。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Artificial intelligence and telemedicine in the field of anaesthesiology, intensive care and pain medicine
The potential role of artificial intelligence in enhancing human life and medical practice is under investigation but the knowledge of the topic among healthcare providers is under-investigated. To investigate knowledge of artificial intelligence in physicians working in the field of anaesthesiology, intensive care, and pain medicine. As secondary outcomes, we investigated the main concerns on the implementation of artificial intelligence. Online survey. Anaesthesiology, intensive care and pain medicine. We invited clinicians specialised in anaesthesia, resuscitation, intensive care and pain medicine who were active members of the European Society of Anaesthesiology and Intensive Care (ESAIC). Online survey from 28 June 2022 to 29 October 2022. Primary outcome was to investigate knowledge of artificial intelligence and telemedicine of participants. A total of 4465 e-mails were sent and 220 specialists, age 46.5 ± 10.2; 128 men (58.2%) responded to the survey. In general, some knowledge of artificial intelligence and machine learning was reported by 207 of 220 (94.1%) and 180 of 220 (81.8%) members, respectively. In anaesthesiology, 168 of 220 (76.4%) and 151 of 220 (68.6%) have heard of artificial intelligence and machine learning. In intensive care, 154 of 220 (70.0%) and 133 of 220 (60.5%) had heard of artificial intelligence and machine learning, while these figures were much lower in pain medicine [artificial intelligence: only 70/220 (31.8%) and machine learning 67/220 (30.5%)]. The main barriers to implementing these tools in clinical practice were: lack of knowledge of algorithms leading to the results; few validation studies available and not enough knowledge of artificial intelligence. Knowledge of telemedicine was reported in 212 of 220 (96.4%) members. Most anaesthesiologists are aware of artificial intelligence and machine learning. General thinking about the application of artificial intelligence in anaesthesiology, intensive care and pain management was positive overall, with most participants not considering this tool as a threat to their profession.
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