{
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  "bibtex": "https://research.draconitic.com/paper/6r8dftm7nh7me.bib",
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  "doi": "10.1007/s13534-026-00615-7",
  "fulltext_url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC13740404/",
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  "pmcid": "PMC13740404",
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  "published": "2026-09-19",
  "publisher": "Springer",
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  "title": "Patient-adaptive and clinically interpretable arrhythmia detection from ECG using lightweight hybrid deep learning",
  "title_text": "Patient-adaptive and clinically interpretable arrhythmia detection from ECG using lightweight hybrid deep learning",
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  "venue": "Biomedical Engineering Letters",
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