Machine learning applied to echocardiographic deformation curves for prediction of heart failure and cardiovascular death.

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Title: Machine learning applied to echocardiographic deformation curves for prediction of heart failure and cardiovascular death.
Authors: Simonsen JØ; Department of Cardiology, Copenhagen University Hospital - Herlev and Gentofte, Hellerup, Denmark.. Electronic address: jako.simonsen@gmail.com., Højlund R; Department of Physics, Technical University of Denmark, Kgs Lyngby, Denmark., Modin D; Department of Cardiology, Copenhagen University Hospital - Herlev and Gentofte, Hellerup, Denmark., Skaarup KG; Department of Cardiology, Copenhagen University Hospital - Herlev and Gentofte, Hellerup, Denmark., Olsen FJ; Department of Cardiology, Copenhagen University Hospital - Herlev and Gentofte, Hellerup, Denmark., Christensen J; Department of Cardiology, Copenhagen University Hospital - Herlev and Gentofte, Hellerup, Denmark., Lassen MCH; Department of Cardiology, Copenhagen University Hospital - Herlev and Gentofte, Hellerup, Denmark., Johansen ND; Department of Cardiology, Copenhagen University Hospital - Herlev and Gentofte, Hellerup, Denmark., Sánchez-Martínez S; Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Spain., Claggett BL; Harvard Medical School, USA., Marott JL; The Copenhagen City Heart Study, Copenhagen University Hospital - Bispebjerg and Frederiksberg, Copenhagen, Denmark., Jensen MT; The Copenhagen City Heart Study, Copenhagen University Hospital - Bispebjerg and Frederiksberg, Copenhagen, Denmark; Steno Diabetes Center Copenhagen, 2730 Herlev, Denmark., Jensen GB; The Copenhagen City Heart Study, Copenhagen University Hospital - Bispebjerg and Frederiksberg, Copenhagen, Denmark., Schnohr P; The Copenhagen City Heart Study, Copenhagen University Hospital - Bispebjerg and Frederiksberg, Copenhagen, Denmark., Møgelvang R; The Copenhagen City Heart Study, Copenhagen University Hospital - Bispebjerg and Frederiksberg, Copenhagen, Denmark; Department of Cardiology, Copenhagen University Hospital - Rigshospitalet, Copenhagen, Denmark., Diederichsen SZ; Department of Cardiology, Copenhagen University Hospital - Rigshospitalet, Copenhagen, Denmark., Xing LY; Department of Cardiology, Copenhagen University Hospital - Herlev and Gentofte, Hellerup, Denmark.; Department of Cardiology, Copenhagen University Hospital - Rigshospitalet, Copenhagen, Denmark., Køber L; Department of Cardiology, Copenhagen University Hospital - Rigshospitalet, Copenhagen, Denmark.; Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark., Svendsen JH; Department of Cardiology, Copenhagen University Hospital - Rigshospitalet, Copenhagen, Denmark.; Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark., Rasmussen S; Novo Nordisk Foundation Center for Basic Metabolic Research Multi-modal Bioinformatics, Denmark., Clemmensen LKH; Applied Mathematics and Computer Science, Technical University of Denmark, Kgs Lyngby, Denmark., Tfelt-Hansen J; Department of Cardiology, Copenhagen University Hospital - Rigshospitalet, Copenhagen, Denmark., Biering-Sørensen T; Department of Cardiology, Copenhagen University Hospital - Herlev and Gentofte, Hellerup, Denmark.; The Copenhagen City Heart Study, Copenhagen University Hospital - Bispebjerg and Frederiksberg, Copenhagen, Denmark; Department of Cardiology, Copenhagen University Hospital - Rigshospitalet, Copenhagen, Denmark.; Department of Biomedical Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.
Source: International journal of cardiology [Int J Cardiol] 2026 Jul 15; Vol. 455, pp. 134481. Date of Electronic Publication: 2026 Apr 09.
Publication Type: Journal Article
Journal Info: Publisher: Elsevier Country of Publication: Netherlands NLM ID: 8200291 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1874-1754 (Electronic) Linking ISSN: 01675273 NLM ISO Abbreviation: Int J Cardiol Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:1874-1754
DOI:10.1016/j.ijcard.2026.134481