{
  "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 ECGx.AI model with those from a shallower $β$-VAE trained on normal PTB-XL ECGs, evaluating downstream classification and Dynamic Time Warping (DTW)-based reconstruction errors. ECGx.AI reached an area under ROC of 0.686 with Random Forest, while the proposed $β$-VAE reached 0.577 with sensitivity of 0.775 with Gradient Boosting. Notably, DTW-reconstruction errors significantly differed between classes in 10 out of 12 leads according to Mann-Whitney U test and help in classification, leading to an area under ROC of 0.643 with Logistic Regression, supporting their potential as markers of scar-related ECG alterations.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": "2609.05294",
  "author_total": 6,
  "authors": [
    {
      "name": "Shayan Sharifi"
    },
    {
      "name": "Riccardo Treu"
    },
    {
      "name": "Ilaria Gandin"
    },
    {
      "name": "Federico Garoia"
    },
    {
      "name": "Marco Merlo"
    },
    {
      "name": "Giulia Cisotto"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/bzt6k9knrbh5r.bib",
  "cited_by": 0,
  "doi": "10.48550/arxiv.2609.05294",
  "fulltext_url": null,
  "id": "bzt6k9knrbh5r",
  "issns": [],
  "landing_url": "https://arxiv.org/abs/2609.05294",
  "language": null,
  "licence": "LicenseRef-arXiv-nonexclusive-1.0",
  "licence_label": "arXiv licence",
  "licence_source": "article",
  "licence_url": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
  "metadata_licence": "CC0-1.0",
  "native_subjects": [
    [
      "arxiv",
      "cs.LG"
    ],
    [
      "arxiv",
      "stat.ML"
    ],
    [
      "openalex",
      "2705|ECG Monitoring and Analysis"
    ]
  ],
  "openalex": "W7211915719",
  "pdf_url": "https://arxiv.org/pdf/2609.05294",
  "pmcid": null,
  "pmid": null,
  "published": "2026-09-04",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/bzt6k9knrbh5r.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:19:25Z",
      "native_id": "2609.05294",
      "source": "arxiv",
      "url": "https://arxiv.org/abs/2609.05294"
    }
  ],
  "subjects": [
    {
      "field": "mathematics",
      "origin": "arxiv:stat.ML",
      "subfield": "statistics"
    }
  ],
  "title": "Learning from VAE Errors to support ECG-based Differential Diagnosis of Myocardial Scar",
  "title_text": "Learning from VAE Errors to support ECG-based Differential Diagnosis of Myocardial Scar",
  "type": "preprint",
  "updated_at": "2026-10-30T12:19:25Z",
  "url": "https://research.draconitic.com/paper/bzt6k9knrbh5r",
  "venue": "arXiv",
  "versions": []
}