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Learning from VAE Errors to support ECG-based Differential Diagnosis of Myocardial Scar

Paper recorded by Signals 4 on 2026-09-04 in cs.LG. Abstract reproduced from arXiv; link to the original below.

Published 2026-09-04 on arXiv · recorded by Signals 4 on 2026-09-07

Category: cs.LG · 机器学习 · first seen 2026-09-07

Abstract

Late Gadolinium Enhancement (LGE) on cardiac magnetic resonance is a key marker of myocardial scar, but its limited accessibility motivates routine ECG-based screening. We evaluated whether $β$-variational autoencoder (VAE)-derived ECG representations can discriminate LGE+ from LGE- cardiomyopathic patients in a local cohort of 300 subjects. We compared 32-dimensional features from the foundation

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#117 most recent of 215 cs.LG papers we have recorded · ↑ newer: LexFlip: A Dissociation Diagnostic for Legal Meaning Preservation Metr · ↓ older: How to Speculate about Uncertainty in Agentic Coding? A Draft-Model Ga
Cite this page: Learning from VAE Errors to support ECG-based Differential Diagnosis of Myocardial Scar: the #117 most recent of 215 cs.LG papers we have recorded (as of 2026-09-04). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/learning-from-vae-errors-to-support-ecg-based-differential-diagnosis-of-myocardi.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
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