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Editorial commentary: Deep learning in cardiology: All models are wrong, but some are useful.

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Title: Editorial commentary: Deep learning in cardiology: All models are wrong, but some are useful.
Authors: Stultz C; Massachusetts Institute of Technology & Massachusetts General Hospital Cambridge, MA, United States. Electronic address: cmstultz@mit.edu.
Source: Trends in cardiovascular medicine [Trends Cardiovasc Med] 2022 Jan; Vol. 32 (1), pp. 42-43. Date of Electronic Publication: 2020 Dec 15.
Publication Type: Editorial; Comment
Journal Info: Publisher: Elsevier Science Publishing Country of Publication: United States NLM ID: 9108337 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1873-2615 (Electronic) Linking ISSN: 10501738 NLM ISO Abbreviation: Trends Cardiovasc Med Subsets: MEDLINE
Database: MEDLINE Ultimate
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PubType: Editorial & Opinion
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        Value: 10.1016/j.tcm.2020.12.001
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      – TitleFull: Editorial commentary: Deep learning in cardiology: All models are wrong, but some are useful.
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              Text: 2022 Jan
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