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Bert Vandenberk1,2, Derek S Chew1, Dinesh Prasana3,4
1Department of Cardiac Sciences, Libin Cardiovascular Institute, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada.
Frontiers in digital health
|July 14, 2023
概括
医疗保健中的人工智能 (AI) 正在迅速发展,但临床实施仍然有限. 本文审查了人工智能方法,并强调了阻碍在医疗保健环境中广泛采用的关键挑战.
科学领域:
- 医疗信息学 医疗信息学
- 医疗人工智能 医疗人工智能
- 数字健康数字健康
背景情况:
- 数据管理和处理方面的重大进步使大数据分析成为可能.
- 医疗保健正在转向个性化医疗,由数字健康倡议推动.
- 人工智能 (AI) 越来越多地被认为是其在医疗应用中的潜力.
研究的目的:
- 审查医疗保健中人工智能的当前方法.
- 确定阻碍AI在医疗保健中的实施的临床和组织挑战.
- 弥合人工智能研究和实际临床应用之间的差距.
主要方法:
- 对医疗保健中人工智能方法的综合文献综述.
- 分析现有的数字健康计划和大数据架构.
- 识别和分类临床AI采用障碍的障碍.
主要成果:
- 许多人工智能方法可用于医疗保健应用.
- 很少有人工智能应用程序成功过渡到常规的临床实践中.
- 人工智能集成存在重大临床和组织障碍.
结论:
- 虽然人工智能对医疗保健具有巨大的前景,但其实际实施面临着巨大的挑战.
- 解决这些临床和组织障碍对于实现AI在医学中的全部潜力至关重要.
- 需要进一步的研究和战略规划,以促进AI在医疗保健中的采用.
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