Identification of hypertrophic cardiomyopathy on electrocardiographic images with deep learning.
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| Title: | Identification of hypertrophic cardiomyopathy on electrocardiographic images with deep learning. |
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| Authors: | Sangha V; Section of Cardiovascular Medicine, Department of Internal Medicine, Yale School of Medicine, New Haven, CT, USA.; Department of Engineering Science, Oxford University, Oxford, UK., Dhingra LS; Section of Cardiovascular Medicine, Department of Internal Medicine, Yale School of Medicine, New Haven, CT, USA., Aminorroaya A; Section of Cardiovascular Medicine, Department of Internal Medicine, Yale School of Medicine, New Haven, CT, USA., Croon PM; Department of Cardiology, Amsterdam Cardiovascular Sciences, Amsterdam University Medical Centre, University of Amsterdam, Amsterdam, The Netherlands., Sikand NV; Section of Cardiovascular Medicine, Department of Internal Medicine, Yale School of Medicine, New Haven, CT, USA., Sen S; Section of Cardiovascular Medicine, Department of Internal Medicine, Yale School of Medicine, New Haven, CT, USA., Martinez MW; Department of Cardiovascular Medicine, Atlantic Health, Morristown Medical Center, Morristown, NJ, USA.; Sports Cardiology and Hypertrophic Cardiomyopathy, Morristown Medical Center, Morristown, NJ, USA., Maron MS; HCM Institute, Tufts Medical Center, Boston, MA, USA., Krumholz HM; Section of Cardiovascular Medicine, Department of Internal Medicine, Yale School of Medicine, New Haven, CT, USA.; Center for Outcomes Research and Evaluation (CORE), Yale New Haven Hospital, New Haven, CT, USA., Asselbergs FW; Department of Cardiology, Amsterdam Cardiovascular Sciences, Amsterdam University Medical Centre, University of Amsterdam, Amsterdam, The Netherlands.; Institute of Health Informatics, University College London, London, UK.; National Institute for Health Research, University College London Hospitals, Biomedical Research Centre, University College London, London, UK., Oikonomou EK; Section of Cardiovascular Medicine, Department of Internal Medicine, Yale School of Medicine, New Haven, CT, USA., Khera R; Section of Cardiovascular Medicine, Department of Internal Medicine, Yale School of Medicine, New Haven, CT, USA. rohan.khera@yale.edu.; Center for Outcomes Research and Evaluation (CORE), Yale New Haven Hospital, New Haven, CT, USA. rohan.khera@yale.edu.; Section of Health Informatics, Department of Biostatistics, Yale School of Public Health, New Haven, CT, USA. rohan.khera@yale.edu. |
| Source: | Nature cardiovascular research [Nat Cardiovasc Res] 2025 Aug; Vol. 4 (8), pp. 991-1000. Date of Electronic Publication: 2025 Jul 22. |
| Publication Type: | Journal Article; Validation Study |
| Journal Info: | Publisher: Springer Nature Country of Publication: England NLM ID: 9918284280206676 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 2731-0590 (Electronic) Linking ISSN: 27310590 NLM ISO Abbreviation: Nat Cardiovasc Res Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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