Interpretation research of deep learning ECG classification results based on classification contribution value

Qiuyang Zhao; Zhanbin Che

doi:10.1117/12.2655870

12 January 2023 Interpretation research of deep learning ECG classification results based on classification contribution value

Qiuyang Zhao, Zhanbin Che

Author Affiliations +

Proceedings Volume 12509, Third International Conference on Intelligent Computing and Human-Computer Interaction (ICHCI 2022); 1250926 (2023) https://doi.org/10.1117/12.2655870
Event: Third International Conference on Intelligent Computing and Human-Computer Interaction (ICHCI 2022), 2022, Guangzhou, China

Abstract

Current ECG classification models focus on the performance of the classification and do not focus on the interpretability of the classification results. This paper proposes an interpretation method for ECG classification results based on deep learning. This method determines the key heartbeat and key ECG time by replacing the heartbeat with a normal heartbeat, setting the fixed-width ECG data segment to zero, and analyzing the changes in the classification result. The classification contribution value of the segment to the classification result, and the heartbeat and electrocardiogram time segment with a larger contribution value to the classification result become the key heartbeat and key time segment for the classification. The experimental results show that the etiological explanation established by this method is highly consistent with the doctor's explanation, which partially solves the interpretation problem of the ECG classification results based on deep learning.

Citation Download Citation

Qiuyang Zhao and Zhanbin Che "Interpretation research of deep learning ECG classification results based on classification contribution value", Proc. SPIE 12509, Third International Conference on Intelligent Computing and Human-Computer Interaction (ICHCI 2022), 1250926 (12 January 2023); https://doi.org/10.1117/12.2655870

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