Author

Thomas Clozel

ORCID 0000-0002-9781-8938Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Research Focus:benchmarking· 2 Approach:deep learning· 2 Organism:human· 2 Research Focus:differential expression· 1 Research Focus:drug response / drug discovery· 1 Assay:imaging· 1 Approach:machine learning (classical)· 1 Assay:spatial transcriptomics· 1

Frequent Co-Authors

Gilles Wainrib· 2 shared Alberto RomagnoniiD· 1 shared Benoît SchmauchiD· 1 shared Charlie SaillardiD· 1 shared Elodie Pronier· 1 shared Julien CaldéraroiD· 1 shared Matahi MoariiiD· 1 shared Meriem SeftaiD· 1 shared

Activity by Year

2018-2019 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

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2 shared papersBioinformatics

Gilles Wainrib

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2 papers

Recent·Most cited

BioinformaticsbioRxivPreprintOct 11, 2019

Transcriptomic learning for digital pathology

Benoît Schmauch, Alberto Romagnoni, Elodie Pronier…·Gilles Wainrib

This paper introduces HE2RNA, a deep learning model that predicts RNA-Seq profiles from histology slides without expert annotation, showing improved performance in predicting microsatellite instability.

11 citations

humanspatial transcriptomics

NeurosciencebioRxivPreprintSep 10, 2018

Brain age prediction of healthy subjects on anatomic MRI with deep learning: going beyond with an \"explainable AI\" mindset

Paul Hérent, Simon Jégou, Gilles Wainrib, Thomas Clozel

This paper develops a preprocessing pipeline and deep learning models to predict brain age from MRI data, finding significant correlations and demonstrating model interpretability.

15 citations

humanimaging