A generalizable deep learning system for cardiac MRI.

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Bibliographic Details
Title: A generalizable deep learning system for cardiac MRI.
Authors: Shad R; Division of Cardiovascular Surgery, Department of Surgery, University of Pennsylvania, Philadelphia, PA, USA. rohan.shad@pennmedicine.upenn.edu., Zakka C; Department of Cardiothoracic Surgery, Stanford University, Stanford, CA, USA., Kaur D; Department of Cardiothoracic Surgery, Stanford University, Stanford, CA, USA., Mathur M; Department of Cardiothoracic Surgery, Stanford University, Stanford, CA, USA., Fong R; Department of Cardiothoracic Surgery, Stanford University, Stanford, CA, USA., Cho J; Department of Cardiothoracic Surgery, Stanford University, Stanford, CA, USA., Filice RW; Department of Radiology, Medstar Georgetown University Hospital, Washington, DC, USA., Mongan J; Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA, USA., Kallianos K; Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA, USA., Khandwala N; Bunkerhill Health, San Francisco, CA, USA., Eng D; Bunkerhill Health, San Francisco, CA, USA., Leipzig M; Department of Cardiothoracic Surgery, Stanford University, Stanford, CA, USA., Witschey WR; Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA., de Feria A; Division of Cardiovascular Medicine, Department of Medicine, University of Pennsylvania, Philadelphia, PA, USA., Ferrari VA; Division of Cardiovascular Medicine, Department of Medicine, University of Pennsylvania, Philadelphia, PA, USA., Ashley EA; Division of Cardiovascular Medicine, Department of Medicine, Genetics, and Biomedical Data Science, Stanford University, Stanford, CA, USA., Acker MA; Division of Cardiovascular Surgery, Department of Surgery, University of Pennsylvania, Philadelphia, PA, USA., Langlotz C; Department of Radiology, Medicine, and Biomedical Data Science, Stanford University, Stanford, CA, USA., Hiesinger W; Department of Cardiothoracic Surgery, Stanford University, Stanford, CA, USA. willhies@stanford.edu.
Source: Nature biomedical engineering [Nat Biomed Eng] 2026 Mar 25. Date of Electronic Publication: 2026 Mar 25.
Publication Type: Journal Article
Journal Info: Publisher: Springer Nature Country of Publication: England NLM ID: 101696896 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 2157-846X (Electronic) Linking ISSN: 2157846X NLM ISO Abbreviation: Nat Biomed Eng Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:2157-846X
DOI:10.1038/s41551-026-01637-3