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1 Ergebnisse
1
Strengthening deep-learning models for intracranial hemorrh..:
Dong-Wan Kang
;
Gi-Hun Park
;
Wi-Sun Ryu
...
https://www.frontiersin.org/articles/10.3389/fneur.2023.1321964/full. , 2023
Link:
https://doi.org/10.3389/fneur.2023.1321964
RT Journal T1 <Title>Strengthening deep-learning models for intracranial hemorrhage detection: strongly annotated computed tomography images and model ensembles</Title> UL https://suche.suub.uni-bremen.de/peid=base-ftdoajarticles:oai:doaj.org_article:5b0897498a2647a29c16f53be079fd6b&Exemplar=1&LAN=DE A1 Dong-Wan Kang A1 Gi-Hun Park A1 Wi-Sun Ryu A1 Dawid Schellingerhout A1 Museong Kim A1 Yong Soo Kim A1 Chan-Young Park A1 Keon-Joo Lee A1 Moon-Ku Han A1 Han-Gil Jeong A1 Dong-Eog Kim PB Frontiers Media S.A. YR 2023 K1 deep-learning algorithm K1 intracranial hemorrhage (ICH) K1 weighted ensemble model K1 strongly annotated dataset K1 neuroimaging K1 Neurology. Diseases of the nervous system K1 RC346-429 JF https://www.frontiersin.org/articles/10.3389/fneur.2023.1321964/full LK http://dx.doi.org/https://doi.org/10.3389/fneur.2023.1321964 DO https://doi.org/10.3389/fneur.2023.1321964 SF ELIB - SuUB Bremen
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