商用人工智能增强数字听觉平台在膜心脏病检测中的外部评估,使用心声回声作为参考标准
Valentina Roquemen-Echeverri1, Peter G Jacobs1, Evan F Shalen2
1Artificial Intelligence for Medical Systems (AIMS) Lab, Department of Biomedical Engineering, Oregon Health & Science University, Portland, OR, USA.
International journal of cardiology
|October 21, 2024
概括
埃科耳分析软件 (EMAS) 对检测膜心脏病 (VHD) 的敏感性较低,根据VHD类型而异. 它不是一个可靠的独立查工具,用于所有VHD诊断.
科学领域:
- 心脏病学 心脏病学
- 人工智能在医学中的应用
- 医学诊断 医学诊断 医学诊断
背景情况:
- 有限的研究评估了膜心脏病 (VHD) 的AI数字听觉精度.
- 人工智能平台用于诊断VHD的临床实用性仍然不确定.
研究的目的:
- 为了外部评估Eko声分析软件 (EMAS) 在检测VHD时的准确性.
- 将EMAS性能与心声回声学 (ECHO) 作为参考标准进行比较.
主要方法:
- 分析了1,029个人的心电图 (PCG) 和ECHO数据.
- 在跨胸部ECHO (TTE) 之前,使用EkoDUO和EkoCORE立声镜记录的PCG.
- 使用TTE诊断计算EMAS灵敏度和特异性.
主要成果:
- 在4081个PCG中,79%适合分析.
- 在EMAS中,用于检测VHD的灵敏度为39.3%,特异性为82.3%.
- 对特定VHD的敏感性:中枢狭窄症 (62.5%),大动脉吐 (75.0%),大动脉狭窄症 (88.9%),中枢狭窄症 (63.3%),中度至重度/重度病例.
结论:
- 在EMAS算法对VHD检测的总体灵敏度有限.
- 在各种VHD类型中,算法灵敏度有所不同.
- EMAS可能有助于诊断特定的VHD病变,但不适合所有VHD查.
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