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A deep learning approach for staging embryonic tissue isolates with small data

Abstract:

Machine learning approaches are becoming increasingly widespread and are now present in most areas of research. Their recent surge can be explained in part due to our ability to generate and store enormous amounts of data with which to train these models. The requirement for large training sets is also responsible for limiting further potential applications of machine learning, particularly in fields where data tend to be scarce such as developmental biology. However, recent research seems to...

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Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1371/journal.pone.0244151

Authors


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Role:
Author
ORCID:
0000-0003-0805-3708
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Institution:
University of Oxford
Division:
MPLS
Department:
Zoology
Oxford college:
Jesus College
Role:
Author
ORCID:
0000-0001-9835-009X
Publisher:
Public Library of Science
Journal:
PLoS ONE More from this journal
Volume:
16
Issue:
1
Article number:
e0244151
Publication date:
2021-01-08
Acceptance date:
2020-12-03
DOI:
EISSN:
1932-6203
Language:
English
Keywords:
Pubs id:
1153026
Local pid:
pubs:1153026
Deposit date:
2021-01-11

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