Koski Eileen, Murphy Judy
IBM TJ Watson Research Center, Yorktown Heights, New York, USA.
IBM Global Healthcare.
Stud Health Technol Inform. 2021 Dec 15;284:295-299. doi: 10.3233/SHTI210726.
The potential value of AI to healthcare, and nursing in particular, ranges from improving quality and efficiency of care to delivering on the promise of personalized and precision medicine. AI systems may become virtually indispensable as ever more data is amassed about every aspect of health. AI can help reduce variability in care, while improving precision, accelerating discovery and reducing disparities. AI can empower patients and potentially allow healthcare professionals to relate to their patients as healers supported by the combined wisdom of the best medical research and analytic technology. There are, however, many challenges to understanding the optimal uses of AI; addressing the technological, systemic, regulatory and attitudinal roadblocks to successful implementation; and integrating AI into the fabric of health care. This paper provides a grounding in the origins and fundamental building blocks of AI, applications in healthcare and for nursing, and the critical challenges facing implementation in healthcare.
人工智能对医疗保健,尤其是护理的潜在价值,涵盖从提高护理质量和效率到实现个性化精准医疗的愿景。随着越来越多关于健康各个方面的数据被积累起来,人工智能系统可能会变得几乎不可或缺。人工智能有助于减少护理差异,同时提高精准度、加速发现并减少差距。人工智能可以赋予患者权力,并有可能使医疗保健专业人员能够以由最佳医学研究和分析技术的综合智慧所支持的治疗者身份与患者建立联系。然而,在理解人工智能的最佳用途、解决成功实施的技术、系统、监管和态度障碍以及将人工智能融入医疗保健结构方面,存在许多挑战。本文提供了人工智能的起源和基本构建要素、在医疗保健和护理中的应用以及在医疗保健实施中面临的关键挑战方面的基础内容。
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