Coronary computed tomography angiography (CTA) has one of the highest diagnostic sensitivities for detection of the significance of coronary artery disease (CAD); however, sensitivity is moderate and may result in increased catheterization rates. We performed an efficacy study to determine whether a trained machine learning algorithm that uses coronary CTA data may improve CAD diagnosis accuracy.

中文翻译：

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卷积神经网络的初步评估，用于从冠状动脉计算机断层扫描血管造影数据对冠状动脉疾病严重程度进行无创评估。

冠状动脉计算机断层造影血管造影（CTA）是检测冠状动脉疾病（CAD）重要性的最高诊断敏感性之一。但是，敏感性中等，可能导致导管插入率增加。我们进行了一项功效研究，以确定使用冠状动脉CTA数据的训练有素的机器学习算法是否可以提高CAD诊断的准确性。