Show simple item record

dc.contributor.authorGrün, Dimitri
dc.contributor.authorRudolph, Felix
dc.contributor.authorGumpfer, Nils
dc.contributor.authorHannig, Jennifer
dc.contributor.authorElsner, Laura K.
dc.contributor.authorJeinsen, Beatrice von
dc.contributor.authorHamm, Christian
dc.contributor.authorRieth, Andreas
dc.contributor.authorGuckert, Michael
dc.contributor.authorKeller, Till
dc.date.accessioned2022-08-30T13:09:29Z
dc.date.available2022-08-30T13:09:29Z
dc.date.issued2021
dc.identifier.urihttps://jlupub.ub.uni-giessen.de//handle/jlupub/7189
dc.identifier.urihttp://dx.doi.org/10.22029/jlupub-6640
dc.language.isoen
dc.rightsNamensnennung 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subject.ddcddc:610
dc.titleIdentifying Heart Failure in ECG Data With Artificial Intelligence - A Meta-Analysis
dc.typearticle
local.affiliationFB 11 - Medizin
local.source.spage1
local.source.epage7
local.source.journaltitleFrontiers in digital health
local.source.volume2
local.source.articlenumber584555
local.source.urihttps://doi.org/10.3389/fdgth.2020.584555


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record