{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,8,15]],"date-time":"2025-08-15T01:03:40Z","timestamp":1755219820891,"version":"3.43.0"},"reference-count":0,"publisher":"IOS Press","isbn-type":[{"value":"9781643686080","type":"electronic"}],"license":[{"start":{"date-parts":[[2025,8,7]],"date-time":"2025-08-07T00:00:00Z","timestamp":1754524800000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,8,7]]},"abstract":"<jats:p>Acute Coronary Syndrome (ACS) is a life-threatening cardiovascular condition where early and accurate diagnosis is critical for effective treatment and improved patient outcomes. This study explores the use of ECG foundation models, specifically ST-MEM and ECG-FM, to enhance ACS risk assessment using prehospital ECG data collected in the ambulances. Both models leverage self-supervised learning (SSL), with ST-MEM using a reconstruction-based approach and ECG-FM employing contrastive learning, capturing unique spatial and temporal ECG features. We evaluate the performance of these models individually and through a fusion approach, where their embeddings are combined for enhanced prediction. Results demonstrate that both foundation models outperform a baseline ResNet-50 model, with the fusion-based approach achieving the highest performance (AUROC: 0.843 \u00b1 0.006, AUCPR: 0.674 \u00b1 0.012). These findings highlight the potential of ECG foundation models for early ACS detection and motivate further exploration of advanced fusion strategies to maximize complementary feature utilization.<\/jats:p>","DOI":"10.3233\/shti250902","type":"book-chapter","created":{"date-parts":[[2025,8,7]],"date-time":"2025-08-07T11:34:38Z","timestamp":1754566478000},"source":"Crossref","is-referenced-by-count":0,"title":["Fusion of ECG Foundation Model Embeddings to Improve Early Detection of Acute Coronary Syndromes"],"prefix":"10.3233","author":[{"given":"Zeyuan","family":"Meng","sequence":"first","affiliation":[{"name":"Department of Computer Science, Emory University, USA"}]},{"given":"Lovely Yeswanth","family":"Panchumarthi","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Emory University, USA"}]},{"given":"Saurabh","family":"Kataria","sequence":"additional","affiliation":[{"name":"School of Nursing, Emory University, USA"}]},{"given":"Alex","family":"Fedorov","sequence":"additional","affiliation":[{"name":"School of Nursing, Emory University, USA"}]},{"given":"Jessica","family":"Z\u00e8gre-Hemsey","sequence":"additional","affiliation":[{"name":"School of Nursing, University of North Carolina at Chapel Hill, USA"}]},{"given":"Xiao","family":"Hu","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Emory University, USA"},{"name":"School of Nursing, Emory University, USA"}]},{"given":"Ran","family":"Xiao","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Emory University, USA"},{"name":"School of Nursing, Emory University, USA"}]}],"member":"7437","container-title":["Studies in Health Technology and Informatics","MEDINFO 2025 \u2014 Healthcare Smart \u00d7 Medicine Deep"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/SHTI250902","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,7]],"date-time":"2025-08-07T11:34:38Z","timestamp":1754566478000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/SHTI250902"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,8,7]]},"ISBN":["9781643686080"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/shti250902","relation":{},"ISSN":["0926-9630","1879-8365"],"issn-type":[{"value":"0926-9630","type":"print"},{"value":"1879-8365","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,8,7]]}}}