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人工智能和机器学习在医院前紧急护理:一个范围审查
Marcel Lucas Chee1, Mark Leonard Chee2, Haotian Huang1
1Faculty of Medicine, Nursing and Health Sciences, Monash University, Melbourne, VIC, Australia.
iScience
|August 23, 2023
概括
人工智能 (AI) 在医院前紧急护理 (PEC) 中表现有希望,在许多应用中表现优于当前的方法. 为了安全的临床实施这些AI工具,需要进一步的前性验证.
科学领域:
- 紧急医疗 紧急医疗
- 人工智能的人工智能
- 医疗信息学 医疗信息学
背景情况:
- 医院前紧急护理 (PEC) 是医疗保健系统的关键组成部分.
- 人工智能 (AI) 的整合为PEC提供了潜在的进步.
- 缺乏对PEC当前人工智能应用的全面了解.
研究的目的:
- 进行对人工智能在医院前急诊护理中的应用进行范围审查.
- 识别该领域的常见AI应用,方法和知识差距.
- 为未来人工智能在PEC的研究和开发提供路线图.
主要方法:
- 采用了一种系统的范围审查方法.
- 分析中包括了106项研究,这些研究调查了PEC中的AI.
- 使用证据地图来识别研究缺口.
主要成果:
- 人工智能在PEC中显示出预测,需求预测和资源优化方面的潜力.
- 在研究比较中,人工智能应用程序经常超过人类临床医生和传统算法.
- 大多数研究都是追溯和内部验证的,表明需要前性验证.
结论:
- 人工智能为增强医院前紧急护理提供了一个有希望的未来.
- 可解释的人工智能对于建立临床医生的信任和促进现实世界的验证至关重要.
- 未来的研究应该专注于前性验证和解决发现的方法差距.
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