{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,25]],"date-time":"2026-08-25T20:25:17Z","timestamp":1787689517274,"version":"build-2784847793"},"publisher-location":"New York, NY, USA","reference-count":40,"publisher":"ACM","content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2026,8,9]]},"DOI":"10.1145\/3770854.3783947","type":"proceedings-article","created":{"date-parts":[[2026,7,31]],"date-time":"2026-07-31T12:07:40Z","timestamp":1785499660000},"page":"2412-2423","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["ECGMind: A Foundation Model for ECG Classification via Dynamic Energy Guidance"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0009-0001-2191-4181","authenticated-orcid":false,"given":"Yuqi","family":"She","sequence":"first","affiliation":[{"name":"East China Normal University, Shanghai, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-1379-4344","authenticated-orcid":false,"given":"Junhao","family":"Huang","sequence":"additional","affiliation":[{"name":"East China Normal University, ShangHai, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0001-0789-1606","authenticated-orcid":false,"given":"Erke","family":"Wang","sequence":"additional","affiliation":[{"name":"East China Normal University, Shanghai, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-6133-9796","authenticated-orcid":false,"given":"Xianhao","family":"Song","sequence":"additional","affiliation":[{"name":"East China Normal University, Shanghai, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3049-9917","authenticated-orcid":false,"given":"Liping","family":"Wang","sequence":"additional","affiliation":[{"name":"East China Normal University, Shanghai, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-5216-2757","authenticated-orcid":false,"given":"Haotong","family":"An","sequence":"additional","affiliation":[{"name":"East China Normal University, shanghai, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-4394-1003","authenticated-orcid":false,"given":"Chen","family":"Xu","sequence":"additional","affiliation":[{"name":"East China Normal University, shanghai, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-2269-6612","authenticated-orcid":false,"given":"Han","family":"Zhang","sequence":"additional","affiliation":[{"name":"East China Normal University, shanghai, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2396-7225","authenticated-orcid":false,"given":"Xuemin","family":"Lin","sequence":"additional","affiliation":[{"name":"Shanghai Jiaotong University, Shanghai, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2026,4,20]]},"reference":[{"key":"e_1_3_2_2_1_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52733.2024.01113"},{"key":"e_1_3_2_2_2_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.bspc.2018.03.003"},{"key":"e_1_3_2_2_3_1","volume-title":"Pretraining ecg data with adversarial masking improves model generalizability for data-scarce tasks. arXiv preprint arXiv:2211.07889","author":"Bo Jessica Y","year":"2022","unstructured":"Jessica Y Bo, Hen-Wei Huang, Alvin Chan, and Giovanni Traverso. 2022. Pretraining ecg data with adversarial masking improves model generalizability for data-scarce tasks. arXiv preprint arXiv:2211.07889 (2022)."},{"key":"e_1_3_2_2_4_1","unstructured":"Tom Brown Benjamin Mann Nick Ryder Melanie Subbiah Jared D Kaplan Prafulla Dhariwal Arvind Neelakantan Pranav Shyam Girish Sastry Amanda Askell et al. 2020. Language models are few-shot learners. Advances in neural information processing systems Vol. 33 (2020) 1877-1901."},{"key":"e_1_3_2_2_5_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.bspc.2022.103493"},{"key":"e_1_3_2_2_6_1","volume-title":"International conference on machine learning. PMLR, 1597-1607","author":"Chen Ting","year":"2020","unstructured":"Ting Chen, Simon Kornblith, Mohammad Norouzi, and Geoffrey Hinton. 2020. A simple framework for contrastive learning of visual representations. In International conference on machine learning. PMLR, 1597-1607."},{"key":"e_1_3_2_2_7_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01549"},{"key":"e_1_3_2_2_8_1","volume-title":"Bert: Pre-training of deep bidirectional transformers for language understanding. arXiv preprint arXiv:1810.04805","author":"Devlin Jacob","year":"2018","unstructured":"Jacob Devlin. 2018. Bert: Pre-training of deep bidirectional transformers for language understanding. arXiv preprint arXiv:1810.04805 (2018)."},{"key":"e_1_3_2_2_9_1","doi-asserted-by":"publisher","DOI":"10.1145\/3580305.3599533"},{"key":"e_1_3_2_2_10_1","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2021\/324"},{"key":"e_1_3_2_2_11_1","volume-title":"Leon Glass, Jeffrey M Hausdorff, Plamen Ch Ivanov, Roger G Mark, Joseph E Mietus, George B Moody, Chung-Kang Peng, and H Eugene Stanley.","author":"Goldberger Ary L","year":"2000","unstructured":"Ary L Goldberger, Luis AN Amaral, Leon Glass, Jeffrey M Hausdorff, Plamen Ch Ivanov, Roger G Mark, Joseph E Mietus, George B Moody, Chung-Kang Peng, and H Eugene Stanley. 2000. PhysioBank, PhysioToolkit, and PhysioNet: components of a new research resource for complex physiologic signals. circulation, Vol. 101, 23 (2000), e215-e220."},{"key":"e_1_3_2_2_12_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.01553"},{"key":"e_1_3_2_2_13_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00975"},{"key":"e_1_3_2_2_14_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.bspc.2023.104772"},{"key":"e_1_3_2_2_15_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV51070.2023.01241"},{"key":"e_1_3_2_2_16_1","volume-title":"International Conference on Machine Learning. PMLR, 5606-5615","author":"Kiyasseh Dani","year":"2021","unstructured":"Dani Kiyasseh, Tingting Zhu, and David A Clifton. 2021. Clocs: Contrastive learning of cardiac signals across space, time, and patients. In International Conference on Machine Learning. PMLR, 5606-5615."},{"key":"e_1_3_2_2_17_1","doi-asserted-by":"publisher","DOI":"10.1145\/3690624.3709405"},{"key":"e_1_3_2_2_18_1","volume-title":"Zero-Shot ECG Classification with Multimodal Learning and Test-time Clinical Knowledge Enhancement. In Forty-first International Conference on Machine Learning.","author":"Liu Che","year":"2024","unstructured":"Che Liu, Zhongwei Wan, Cheng Ouyang, Anand Shah, Wenjia Bai, and Rossella Arcucci. 2024. Zero-Shot ECG Classification with Multimodal Learning and Test-time Clinical Knowledge Enhancement. In Forty-first International Conference on Machine Learning."},{"key":"e_1_3_2_2_19_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.00605"},{"key":"e_1_3_2_2_20_1","volume-title":"Foundation models for cardiovascular disease detection via biosignals from digital stethoscopes. npj Cardiovascular Health","author":"Mathew George","year":"2024","unstructured":"George Mathew, Daniel Barbosa, John Prince, and Subramaniam Venkatraman. 2024. Foundation models for cardiovascular disease detection via biosignals from digital stethoscopes. npj Cardiovascular Health, Vol. 1, 1 (2024), 25."},{"key":"e_1_3_2_2_21_1","volume-title":"Self-supervised representation learning from 12-lead ECG data. Computers in biology and medicine","author":"Mehari Temesgen","year":"2022","unstructured":"Temesgen Mehari and Nils Strodthoff. 2022. Self-supervised representation learning from 12-lead ECG data. Computers in biology and medicine, Vol. 141 (2022), 105114."},{"key":"e_1_3_2_2_22_1","doi-asserted-by":"publisher","DOI":"10.1109\/MeMeA.2018.8438739"},{"key":"e_1_3_2_2_23_1","volume-title":"International Conference on Learning Representations.","author":"Na Yeongyeon","year":"2024","unstructured":"Yeongyeon Na, Minje Park, Yunwon Tae, and Sunghoon Joo. 2024. Guiding Masked Representation Learning to Capture Spatio-Temporal Relationship of Electrocardiogram. In International Conference on Learning Representations."},{"key":"e_1_3_2_2_24_1","volume-title":"International Conference on Learning Representations.","author":"Nie Yuqi","year":"2023","unstructured":"Yuqi Nie, Nam H. Nguyen, Phanwadee Sinthong, and Jayant Kalagnanam. 2023. A Time Series is Worth 64 Words: Long-term Forecasting with Transformers. In International Conference on Learning Representations."},{"key":"e_1_3_2_2_25_1","volume-title":"International conference on machine learning. PMLR, 8748-8763","author":"Radford Alec","year":"2021","unstructured":"Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, et al., 2021. Learning transferable visual models from natural language supervision. In International conference on machine learning. PMLR, 8748-8763."},{"key":"e_1_3_2_2_26_1","volume-title":"Zenodo","volume":"9","author":"Ribeiro Ant\u00f4nio H","year":"2021","unstructured":"Ant\u00f4nio H Ribeiro, GM Paixao, Emilly M Lima, M Horta Ribeiro, Marcelo M Pinto Filho, Paulo R Gomes, Derick M Oliveira, Wagner Meira Jr, Th\u00f6mas B Schon, and Antonio Luiz P Ribeiro. 2021. CODE-15%: A large scale annotated dataset of 12-lead ECGs. Zenodo, Jun, Vol. 9 (2021)."},{"key":"e_1_3_2_2_27_1","volume-title":"Primary prevention of cardiovascular disease: A review of contemporary guidance and literature. JRSM cardiovascular disease","author":"Stewart Jack","year":"2017","unstructured":"Jack Stewart, Gavin Manmathan, and Peter Wilkinson. 2017. Primary prevention of cardiovascular disease: A review of contemporary guidance and literature. JRSM cardiovascular disease, Vol. 6 (2017), 2048004016687211."},{"key":"e_1_3_2_2_28_1","volume-title":"Icentia11k: An unsupervised representation learning dataset for arrhythmia subtype discovery. arXiv preprint arXiv:1910.09570","author":"Tan Shawn","year":"2019","unstructured":"Shawn Tan, Guillaume Androz, Ahmad Chamseddine, Pierre Fecteau, Aaron Courville, Yoshua Bengio, and Joseph Paul Cohen. 2019. Icentia11k: An unsupervised representation learning dataset for arrhythmia subtype discovery. arXiv preprint arXiv:1910.09570 (2019)."},{"key":"e_1_3_2_2_29_1","doi-asserted-by":"publisher","DOI":"10.1161\/CIR.0000000000000950"},{"key":"e_1_3_2_2_30_1","volume-title":"a large publicly available electrocardiography dataset. Scientific data","author":"Wagner Patrick","year":"2020","unstructured":"Patrick Wagner, Nils Strodthoff, Ralf-Dieter Bousseljot, Dieter Kreiseler, Fatima I Lunze, Wojciech Samek, and Tobias Schaeffter. 2020. PTB-XL, a large publicly available electrocardiography dataset. Scientific data, Vol. 7, 1 (2020), 1-15."},{"key":"e_1_3_2_2_31_1","doi-asserted-by":"publisher","DOI":"10.1145\/3580305.3599812"},{"key":"e_1_3_2_2_32_1","volume-title":"Daniel C Casey, Fiona J Charlson, Alan Zian Chen, Matthew M Coates, et al.","author":"Wang Haidong","year":"2016","unstructured":"Haidong Wang, Mohsen Naghavi, Christine Allen, Ryan M Barber, Zulfiqar A Bhutta, Austin Carter, Daniel C Casey, Fiona J Charlson, Alan Zian Chen, Matthew M Coates, et al., 2016. Global, regional, and national life expectancy, all-cause mortality, and cause-specific mortality for 249 causes of death, 1980-2015: a systematic analysis for the Global Burden of Disease Study 2015. The lancet, Vol. 388, 10053 (2016), 1459-1544."},{"key":"e_1_3_2_2_33_1","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2023.3272153"},{"key":"e_1_3_2_2_34_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ejim.2019.11.018"},{"key":"e_1_3_2_2_35_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-024-09486-4"},{"key":"e_1_3_2_2_36_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v36i8.20881"},{"key":"e_1_3_2_2_37_1","first-page":"1","article-title":"Maefe: Masked autoencoders family of electrocardiogram for self-supervised pretraining and transfer learning","volume":"72","author":"Zhang Huaicheng","year":"2022","unstructured":"Huaicheng Zhang, Wenhan Liu, Jiguang Shi, Sheng Chang, Hao Wang, Jin He, and Qijun Huang. 2022. Maefe: Masked autoencoders family of electrocardiogram for self-supervised pretraining and transfer learning. IEEE Transactions on Instrumentation and Measurement, Vol. 72 (2022), 1-15.","journal-title":"IEEE Transactions on Instrumentation and Measurement"},{"key":"e_1_3_2_2_38_1","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2023.3292066"},{"key":"e_1_3_2_2_39_1","volume-title":"Hesham El-Askary, Anthony Chang, Louis Ehwerhemuepha, Islam Abudayyeh, Alexander Barrett, et al.","author":"Zheng Jianwei","year":"2020","unstructured":"Jianwei Zheng, Huimin Chu, Daniele Struppa, Jianming Zhang, Sir Magdi Yacoub, Hesham El-Askary, Anthony Chang, Louis Ehwerhemuepha, Islam Abudayyeh, Alexander Barrett, et al., 2020a. Optimal multi-stage arrhythmia classification approach. Scientific reports, Vol. 10, 1 (2020), 2898."},{"key":"e_1_3_2_2_40_1","volume-title":"A 12-lead electrocardiogram database for arrhythmia research covering more than 10,000 patients. Scientific data","author":"Zheng Jianwei","year":"2020","unstructured":"Jianwei Zheng, Jianming Zhang, Sidy Danioko, Hai Yao, Hangyuan Guo, and Cyril Rakovski. 2020b. A 12-lead electrocardiogram database for arrhythmia research covering more than 10,000 patients. Scientific data, Vol. 7, 1 (2020), 48."}],"event":{"name":"KDD '26: The 32nd ACM SIGKDD Conference on Knowledge Discovery and Data Mining","location":"Jeju Island Republic of Korea","sponsor":["SIGMOD ACM Special Interest Group on Management of Data","SIGKDD ACM Special Interest Group on Knowledge Discovery in Data"]},"container-title":["Proceedings of the 32nd ACM SIGKDD Conference on Knowledge Discovery and Data Mining V.1"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3770854.3783947","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,8,25]],"date-time":"2026-08-25T20:15:21Z","timestamp":1787688921000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3770854.3783947"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,4,20]]},"references-count":40,"alternative-id":["10.1145\/3770854.3783947","10.1145\/3770854"],"URL":"https:\/\/doi.org\/10.1145\/3770854.3783947","relation":{},"subject":[],"published":{"date-parts":[[2026,4,20]]},"assertion":[{"value":"2026-04-20","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}