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oai:serval.unil.ch:BIB_A62E636357DA
2024-03-23T02:47:43Z
serval:BIB_A62E636357DA
A weakly supervised deep learning approach for label-free imaging flow-cytometry-based blood diagnostics.
10.1016/j.crmeth.2021.100094
35474892
Otesteanu
C.F.
author
Ugrinic
M.
author
Holzner
G.
author
Chang
Y.T.
author
Fassnacht
C.
author
Guenova
E.
author
Stavrakis
S.
author
deMello
A.
author
Claassen
M.
author
article
2021-10-25
Cell reports methods
2667-2375
2667-2375
journal
1
6
100094
Materials Chemistry
Economics and Econometrics
Media Technology
Forestry
Sézary syndrome
cancer cell imaging
deep learning
high-throughput imaging
image flow cytometry
machine learning
peripheral blood mononuclear samples
weakly supervised learning
eng
60_published
true
peer-reviewed
Publication types: Journal Article
Publication Status: epublish
https://serval.unil.ch/notice/serval:BIB_A62E636357DA
https://serval.unil.ch/resource/serval:BIB_A62E636357DA.P001/REF.pdf
Restricted: indefinite embargo
Creative Commons : Attribution 4.0 International