Multiscale classification of heart failure phenotypes by unsupervised clustering of unstructured electronic medical record data.

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Title: Multiscale classification of heart failure phenotypes by unsupervised clustering of unstructured electronic medical record data.
Authors: Nagamine T; Droice Research, New York, NY, USA., Gillette B; Department of Surgery, NYU Langone Hospital Long Island, Mineola, NY, USA.; Department of Foundations of Medicine, NYU Long Island School of Medicine, Mineola, NY, USA., Pakhomov A; Droice Research, New York, NY, USA., Kahoun J; Droice Research, New York, NY, USA.; Clinical Informatics, CityMD, New York, NY, USA., Mayer H; Clinical Pharmacometrics, Bayer AG, Wuppertal, Germany., Burghaus R; Clinical Pharmacometrics, Bayer AG, Wuppertal, Germany., Lippert J; Clinical Pharmacometrics, Bayer AG, Wuppertal, Germany., Saxena M; Droice Research, New York, NY, USA. mayur@droicelabs.com.
Source: Scientific reports [Sci Rep] 2020 Dec 07; Vol. 10 (1), pp. 21340. Date of Electronic Publication: 2020 Dec 07.
Publication Type: Journal Article
Journal Info: Publisher: Nature Publishing Group Country of Publication: England NLM ID: 101563288 Publication Model: Electronic Cited Medium: Internet ISSN: 2045-2322 (Electronic) Linking ISSN: 20452322 NLM ISO Abbreviation: Sci Rep Subsets: MEDLINE
Database: MEDLINE Ultimate
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ISSN:2045-2322
DOI:10.1038/s41598-020-77286-6