A Deep Learning Model for Inferring Elevated Pulmonary Capillary Wedge Pressures From the 12-Lead Electrocardiogram.

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Bibliographic Details
Title: A Deep Learning Model for Inferring Elevated Pulmonary Capillary Wedge Pressures From the 12-Lead Electrocardiogram.
Authors: Schlesinger DE; Harvard-MIT Division of Health Sciences and Technology, MIT, Cambridge, Massachusetts, USA.; Institute for Medical Engineering and Science, MIT, Cambridge, Massachusetts, USA.; Research Laboratory of Electronics, Computer Science & Artificial Intelligence Laboratory, MIT, Cambridge, Massachusetts, USA., Diamant N; Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA., Raghu A; Research Laboratory of Electronics, Computer Science & Artificial Intelligence Laboratory, MIT, Cambridge, Massachusetts, USA.; Department of Electrical Engineering and Computer Science, MIT, Cambridge, Massachusetts, USA., Reinertsen E; Research Laboratory of Electronics, Computer Science & Artificial Intelligence Laboratory, MIT, Cambridge, Massachusetts, USA.; Division of Cardiology, Massachusetts General Hospital, Boston, Massachusetts, USA., Young K; Harvard-MIT Division of Health Sciences and Technology, MIT, Cambridge, Massachusetts, USA., Batra P; Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA., Pomerantsev E; Division of Cardiology, Massachusetts General Hospital, Boston, Massachusetts, USA., Stultz CM; Harvard-MIT Division of Health Sciences and Technology, MIT, Cambridge, Massachusetts, USA.; Institute for Medical Engineering and Science, MIT, Cambridge, Massachusetts, USA.; Research Laboratory of Electronics, Computer Science & Artificial Intelligence Laboratory, MIT, Cambridge, Massachusetts, USA.; Department of Electrical Engineering and Computer Science, MIT, Cambridge, Massachusetts, USA.; Division of Cardiology, Massachusetts General Hospital, Boston, Massachusetts, USA.
Source: JACC. Advances [JACC Adv] 2022 Mar 18; Vol. 1 (1), pp. 100003. Date of Electronic Publication: 2022 Mar 18 (Print Publication: 2022).
Publication Type: Journal Article
Journal Info: Publisher: Elsevier Inc Country of Publication: United States NLM ID: 9918419284106676 Publication Model: eCollection Cited Medium: Internet ISSN: 2772-963X (Electronic) Linking ISSN: 2772963X NLM ISO Abbreviation: JACC Adv Subsets: PubMed not MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:2772-963X
DOI:10.1016/j.jacadv.2022.100003