כתבה
arXiv cs.LG ·
MS-ECG-FM: כלי יסודי חדש לאבחון אלקטרוקרדיוגרפי
MS-ECG-FM: Towards a More Universal Electrocardiogram Foundation Model for Health Monitoring using Multi-source Contrastive Learning
אבחון אלקטרוקרדיוגרפי חדש, MS-ECG-FM, המוכשר דרך התאמה חופפת לסוגי הערות רפואיות שונים.
תקציר מקורי באנגליתarXiv:2610.07662v1 Announce Type: new Abstract: Electrocardiography (ECG) records the electrical activity of the heart, aiding diagnosis by detecting abnormalities in cardiac function. ECG foundation models have demonstrated promising results, but are limited by a reliance on ECG interpretation reports as their sole supervision. Because interpretation reports only capture the subset of waveform information routinely recognized by clinicians, this constrains representation learning to overlook the broader diagnostic signals present in ECG. We introduce a new ECG foundation model --- MS-ECG-FM --- that is trained through contrastive alignment to multiple distinct clinical note types, including ECG, echocardiography, radiology, and discharge reports. We evaluate MS-ECG-FM on an extended set o
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