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Quality of reporting in AI cardiac MRI segmentation studies..:

Samer Alabed ; Ahmed Maiter ; Mahan Salehi...
https://www.frontiersin.org/articles/10.3389/fcvm.2022.956811/full. , 2022

Link: https://doi.org/10.3389/fcvm.2022.956811

RT Journal
T1 <Title>Quality of reporting in AI cardiac MRI segmentation studies – A systematic review and recommendations for future studies</Title>

UL https://suche.suub.uni-bremen.de/peid=base-ftdoajarticles:oai:doaj.org_article:f853fdb9f42a4572a2698f55608f6a92&Exemplar=1&LAN=DE
				
A1 Samer Alabed
A1 Ahmed Maiter
A1 Mahan Salehi
A1 Aqeeb Mahmood
A1 Sonali Daniel
A1 Sam Jenkins
A1 Marcus Goodlad
A1 Michael Sharkey
A1 Michail Mamalakis
A1 Vera Rakocevic
A1 Krit Dwivedi
A1 Hosamadin Assadi
A1 Jim M. Wild
A1 Haiping Lu
A1 Declan P. O'Regan
A1 Rob J. van der Geest
A1 Pankaj Garg
A1 Andrew J. Swift
PB Frontiers Media S.A.
YR 2022
K1 artificial intelligence
K1 machine learning
K1 cardiac MRI
K1 segmentation
K1 systematic review
K1 quality
K1 Diseases of the circulatory (Cardiovascular) system
K1 RC666-701
JF https://www.frontiersin.org/articles/10.3389/fcvm.2022.956811/full
LK http://dx.doi.org/https://doi.org/10.3389/fcvm.2022.956811
DO https://doi.org/10.3389/fcvm.2022.956811
SF ELIB - SuUB Bremen

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