深度学习有助于在心电图信号上早期检测高血压介导的心脏变化
Chengwei Liang1,2, Fan Yang1,2,3, Xiaobing Huang4
1Department of Automation, Xiamen University, Xiamen, Fujian, China.
概括
电心电图 (ECG) 信号可以检测高血压引起的微妙心脏变化,优于心脏病学家. 一个深度学习模型确定了特定的心电图段,R波和P波,与高血压有关,用于早期诊断.
科学领域:
- 心脏病学 心脏病学
- 人工智能的人工智能
- 医学诊断 医学诊断 医学诊断
背景情况:
- 动脉高血压是心血管疾病的重要危险因素.
- 心脏超声波经常错过了高血压引起的早期,微妙的心脏结构变化.
- 电心电图 (ECG) 信号反映了心脏的电活动,并受到结构变化的影响.
研究的目的:
- 为了研究心电图信号是否能检测到微妙的,高血压中介的心脏变化.
- 开发一个深度学习模型来预测ECG的高血压.
- 为了确定与高血压相关的特定心电图段.
主要方法:
- 收集了12个导向ECG的大量数据集 (210,120 + 812条记录).
- 开发了MML-Net,这是一个多分支,多规模的LSTM深度学习网络,用于高血压预测.
- 利用了ECG-XAI,这是一种用于识别高血压相关心电图段的AI解释管道.
主要成果:
- MML-Net实现了82%的回忆和87%的测试精度,超过了心脏病学家的视觉检查 (30-50%的回忆).
- 独立测试显示,MML-Net实现了80%的回忆率和82%的精度.
- ECG-XAI确定了与高血压相关的R波和P波段.
结论:
- 电脑心电图信号对高血压引起的早期,微妙的心脏结构变化敏感.
- 拟议的深度学习框架表明了早期高血压诊断的潜力.
- 对心电图的AI分析可以识别特定的高血压心脏变化,帮助临床实践.
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An electrocardiogram (ECG) is a diagnostic tool for identifying cardiac conditions such as arrhythmias, conduction abnormalities, and myocardial ischemia.
Definition
An electrocardiogram (ECG) visualizes the heart's electrical activity by tracing the electrical movement associated with each heartbeat on a graph or monitor. As the heart beats, an electrical wave passes through it, correlating with the cardiac cycle events.
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An ECG utilizes electrodes on the skin...
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