单位：[1]Department of Cardiovascular Surgery, Tongji Hospital of Tongji Medical College of Huazhong University of Science and Technology, Wuhan, Hubei, China.外科学系心脏大血管外科华中科技大学同济医学院附属同济医院[2]Division of Cardiology, Department of Internal Medicine, Tongji Hospital of Tongji Medical College of Huazhong University of Science and Technology, Wuhan, Hubei, China.内科学系大内科心血管内科华中科技大学同济医学院附属同济医院[3]Department of Computer Center, Tongji Hospital of Tongji Medical College of Huazhong University of Science and Technology, Wuhan, Hubei, China.党政职能科室计算机中心华中科技大学同济医学院附属同济医院
Background: Aortic dissection (AD) is frequently associated with abnormalities in electrocardiographic findings. The advancements in medical technology present an opportunity to leverage these observations for enhanced patient diagnosis and care.
Objectives: This study aimed to develop a deep learning artificial intelligence (AI) model for AD detection using electrocardiogram (ECG) and introduce the AI-Aortic-Dissection-ECG (AADE) score, providing clinicians a measure correlating with AD severity.
Methods: From a cohort of 1878 patients, including 313 with AD, and a chest pain control group of 313, we created training and validation subsets (7:3 ratio). A convolutional neural networks (CNN) model was trained for AD detection, with performance metrics like accuracy and F1 score monitored. The AI-derived AADE score (0–1) was investigated against clinical parameters and ECG features over a median follow-up of 21.2 months.
Results: The CNN model demonstrated robust performance with an accuracy of 0.93 and F1 score of 0.93. and an accuracy of 0.871 with an F1 score of 0.867 for the chest pain group. The AADE score showed correlations with specific ECG patterns and revealed that higher scores aligned with increased mortality risks.
Conclusions: Our CNN-based AI model offers a promising approach for AD detection using ECG. The AADE score, anchored in AI, can serve as a pivotal tool in refining clinical assessments and management strategies.
第一作者单位：[1]Department of Cardiovascular Surgery, Tongji Hospital of Tongji Medical College of Huazhong University of Science and Technology, Wuhan, Hubei, China.
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推荐引用方式(GB/T 7714)：
Zhou Minghe,Lei Lei,Chen Wei,et al.Deep learning-based diagnosis of aortic dissection using electrocardiogram: Development, validation, and clinical implications of the AADE Score[J].KARDIOLOGIA POLSKA.2024,82(1):63-71.doi:10.33963/v.phj.98880.
APA：
Zhou Minghe,Lei Lei,Chen Wei,Luo Qiushi,Li Jin...&Pan Youmin.(2024).Deep learning-based diagnosis of aortic dissection using electrocardiogram: Development, validation, and clinical implications of the AADE Score.KARDIOLOGIA POLSKA,82,(1)
MLA：
Zhou Minghe,et al."Deep learning-based diagnosis of aortic dissection using electrocardiogram: Development, validation, and clinical implications of the AADE Score".KARDIOLOGIA POLSKA 82..1(2024):63-71
