对心力衰竭进行个性化管理,使用保存的喷射分数来治疗心力衰竭
Chang-Yi Lin1, Heng-You Sung1, Ying-Ju Chen2
1Division of Cardiology, Department of Internal Medicine, MacKay Memorial Hospital, No. 92, Sec. 2, Zhongshan N. Road, Taipei 10449, Taiwan.
Journal of personalized medicine
|May 27, 2023
概括
人工智能 (AI) 可以识别心力衰竭的不同患者群体,其中保留喷射分数 (HFpEF). 需要进一步的研究来将人工智能驱动的表型化纳入临床实践,以更好地管理HFpEF.
科学领域:
- 心脏病学 心脏病学
- 医疗信息学 医疗信息学
- 人工智能的人工智能
背景情况:
- 由于多种潜在机制和并发症,心力衰竭与保存的喷射分数 (HFpEF) 呈现出不同的临床表型.
- 了解这些表型对于推进HFpEF病理生理学,治疗策略和患者结果至关重要.
研究的目的:
- 探索人工智能 (AI) 在使用多维数据的HFpEF表型化方面的潜力.
- 突出AI能力与HFpEF当前临床实践指南之间的差距.
主要方法:
- 基于人工智能的表型化利用临床,生物标志物和成像数据.
- 对现有数据的分析,以确定不同的HFpEF表型.
主要成果:
- 累积的数据表明,人工智能可以有效地表型HFpEF患者.
- 目前的指导方针和共识缺乏将人工智能驱动的表型化纳入日常实践.
结论:
- 基于人工智能的表型化对推进HFpEF管理具有前景.
- 需要进一步的研究来验证AI的发现,并为HFpEF标准化临床实施.
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