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A formal validation of a deep learning-based automated workflow for the interpretation of the echocardiogram

Authors :
Jasper Tromp
David Bauer
Brian L. Claggett
Matthew Frost
Mathias Bøtcher Iversen
Narayana Prasad
Mark C. Petrie
Martin G. Larson
Justin A. Ezekowitz
Scott D. Solomon
Source :
Nature Communications, Vol 13, Iss 1, Pp 1-9 (2022)
Publication Year :
2022
Publisher :
Nature Portfolio, 2022.

Abstract

Deep learning can automate the interpretation of medical imaging tests. Here, the authors formally assess the interchangeability of deep learning algorithms with expert human measurements for interpreting echocardiographic studies.

Subjects

Subjects :
Science

Details

Language :
English
ISSN :
20411723
Volume :
13
Issue :
1
Database :
Directory of Open Access Journals
Journal :
Nature Communications
Publication Type :
Academic Journal
Accession number :
edsdoj.399be6a8039f45d19de79a68ec302dd6
Document Type :
article
Full Text :
https://doi.org/10.1038/s41467-022-34245-1