Artificial Intelligence-Enhanced Electrocardiogram Models for Detection of Left Ventricular Dysfunction: A Comparison Study.
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| Title: | Artificial Intelligence-Enhanced Electrocardiogram Models for Detection of Left Ventricular Dysfunction: A Comparison Study. |
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| Authors: | Croon PM; Department of Cardiology, Amsterdam Cardiovascular Science, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands; Section of Cardiovascular Medicine, Department of Internal Medicine, Yale University, New Haven, USA., Boonstra MJ; Department of Cardiology, Amsterdam Cardiovascular Science, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands; Department of Medical Informatics, Amsterdam UMC Location University of Amsterdam, Amsterdam, Netherlands., Allaart CP; Department of Cardiology, Amsterdam Cardiovascular Science, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands., Arends BKO; Department of Cardiology, University Medical Center Utrecht, Utrecht, The Netherlands., Dhingra LS; Section of Cardiovascular Medicine, Department of Internal Medicine, Yale University, New Haven, USA., Huang YC; Division of Cardiology, Chang Gung Memorial Hospital, Taoyuan, Taiwan., Mast T; Department of Cardiology, Catharina Hospital Eindhoven, Eindhoven, The Netherlands., Khera R; Section of Cardiovascular Medicine, Department of Internal Medicine, Yale University, New Haven, USA; Center for Outcomes Research and Evaluation, Yale New Haven Hospital, New Haven, Connecticut, USA; Section of Health Informatics, Department of Biostatistics, Yale School of Public Health, New Haven, Connecticut, USA., Kuo CF; School of Medicine, College of Medicine, Chang Gung University, Taoyuan, Taiwan; Division of Rheumatology, Allergy and Immunology, Chang Gung Memorial Hospital, Taoyuan, Taiwan., Kwon JM; Digital Healthcare Institute, Sejong Medical Research Institute, Bucheon, Republic of Korea; Medical AI Co., Ltd., Seoul, Republic of Korea., Lee HS; Digital Healthcare Institute, Sejong Medical Research Institute, Bucheon, Republic of Korea; Medical AI Co., Ltd., Seoul, Republic of Korea., Lee MS; Digital Healthcare Institute, Sejong Medical Research Institute, Bucheon, Republic of Korea; Medical AI Co., Ltd., Seoul, Republic of Korea., van de Leur RR; Department of Cardiology, University Medical Center Utrecht, Utrecht, The Netherlands., Liu ZY; Center for Artificial Intelligence in Medicine, Chang Gung Memorial Hospital, Taoyuan, Taiwan., Oikonomou EK; Section of Cardiovascular Medicine, Department of Internal Medicine, Yale University, New Haven, USA., Selder JL; Department of Cardiology, Amsterdam Cardiovascular Science, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands., Winter MM; Department of Cardiology, Amsterdam Cardiovascular Science, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands., Asselbergs FW; Department of Cardiology, Amsterdam Cardiovascular Science, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, The Netherlands; Institute of Health Informatics, University College London, London, United Kingdom; The National Institute for Health Research UCL Hospitals Biomedical Research Centre, University College London, London, United Kingdom. Electronic address: f.w.asselbergs@amsterdamumc.nl. |
| Source: | JACC. Advances [JACC Adv] 2026 Feb; Vol. 5 (2), pp. 102572. Date of Electronic Publication: 2026 Jan 20. |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Elsevier Inc Country of Publication: United States NLM ID: 9918419284106676 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 2772-963X (Electronic) Linking ISSN: 2772963X NLM ISO Abbreviation: JACC Adv Subsets: PubMed not MEDLINE |
| Database: | MEDLINE Ultimate |
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