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In Silico Clinical Trials for Cardiovascular Disease
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人工智能在多变性心肌病中的应用:转折和漏洞
Giorgia Panichella1,2, Manuel Garofalo1,2, Laura Sasso2
1Department of Experimental and Clinical Medicine, University of Florence, Viale Morgagni, 63, Florence 50134, Italy.
European heart journal. Digital health
|September 23, 2025
概括
人工智能 (AI) 正在通过改进诊断,风险分层和个性化治疗来彻底改变多变性心肌病 (HCM) 护理. 人工智能应用程序分析复杂的数据,用于精确的患者管理和在HCM发现药物.
科学领域:
- 心脏病学 心脏病学
- 生物医学工程 生物医学工程
- 医疗信息学 医疗信息学
背景情况:
- 超性心肌病 (HCM) 尽管取得了进展,但仍存在诊断和治疗方面的挑战.
- 准确的风险分层和个性化治疗仍然是HCM管理中的关键未满足需求.
研究的目的:
- 审查人工智能 (AI) 在缩性心肌病中的当前和潜在应用.
- 探索AI在提高诊断,风险分层和个性化治疗策略方面的作用.
- 讨论人工智能的整合,包括数字双胞胎和in silico试验,进入临床实践和HCM的药物发现.
主要方法:
- 使用人工智能对诊断成像 (心电图,心声,心肺复合镜) 的分析,以提高准确性.
- 开发用于风险分层和治疗决策的多式人工智能方法.
- 利用人工智能驱动的数字双胞胎平台和in silico试验进行患者特定的疾病模拟和临床前评估.
主要成果:
- 人工智能通过分析复杂的成像数据和识别微妙的变异来提高HCM的诊断准确性.
- 由人工智能驱动的策略可以改善风险分层和监测心脏肌抑制剂等新型疗法.
- 将遗传数据与人工智能的整合有助于识别有风险的个体并预测疾病的进展.
结论:
- 人工智能为精确的诊断,风险分层和个性化治疗提供了变革性的潜力.
- 人工智能,包括数字双胞胎技术,可以彻底改变医疗保健领域的药物发现和患者护理途径.
- 解决伦理问题和为可信的人工智能制定准则对于在HCM管理中得到广泛采用至关重要.
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