ECGGAN: A Framework for Effective and Interpretable Electrocardiogram Anomaly Detection - researchr publication authors

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Huazhang Wang, Zhaojing Luo, James W. L. Yip, Chuyang Ye, Meihui Zhang 0001. ECGGAN: A Framework for Effective and Interpretable Electrocardiogram Anomaly Detection. In Ambuj Singh, Yizhou Sun, Leman Akoglu, Dimitrios Gunopulos, Xifeng Yan, Ravi Kumar 0001, Fatma Ozcan, Jieping Ye, editors, Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, KDD 2023, Long Beach, CA, USA, August 6-10, 2023. pages 5071-5081, ACM, 2023. [doi]

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