通过常规的心脏扫描和记录, 一个人工智能工具可以预测心力衰竭的发病情况,准确率高达85%, 比较优于旧方法. An AI tool using routine heart scans and records predicts advanced heart failure with 85% accuracy, outperforming older methods.

由威尔康奈尔医学院和其他机构的研究人员开发的一种人工智能系统通过分析常规心脏超声波和电子健康记录,准确预测晚期的心力衰竭,在识别高风险患者方面以85%的精度超过以前的方法. An AI system developed by researchers from Weill Cornell Medicine and other institutions accurately predicts advanced heart failure by analyzing routine cardiac ultrasounds and electronic health records, outperforming previous methods with 85% accuracy in identifying high-risk patients. 该工具可以估计高峰氧耗 - 一个关键的诊断措施, 无需专门的心肺运动测试, 这种检查通常在主要医疗中心以外无法获得. The tool estimates peak oxygen consumption—a key diagnostic measure—without requiring specialized cardiopulmonary exercise testing, which is often unavailable outside major medical centers. 在另一项研究中,另一个AI算法在84%的病例中检测到没有ST升高的闭塞性心脏病发作,显著超过标准临床方法. In a separate study, another AI algorithm detected occlusive heart attacks without ST elevation in 84% of cases, significantly outperforming standard clinical methods. 这两项研究在2026年ESC急性心血管保健大会上发表,表明人工智能可以改善早期诊断和治疗机会,尽管在广泛使用之前需要进一步验证. Both studies, presented at the 2026 ESC Acute CardioVascular Care congress, suggest AI could improve early diagnosis and treatment access, though further validation is needed before widespread use.