Author

Charles Maussion

ORCID 0000-0003-2266-5276Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Approach:deep learning· 2 Organism:human· 2 Research Focus:cell type annotation· 1 Research Focus:differential expression· 1 Assay:imaging· 1 Assay:spatial transcriptomics· 1

Frequent Co-Authors

Alberto RomagnoniiD· 1 shared Alexandra HardyiD· 1 shared Anca Mera· 1 shared Andre L. MoreiraiD· 1 shared Aurélie SwalduziD· 1 shared Benoît SchmauchiD· 1 shared Brooke E. HowittiD· 1 shared Caroline TruntzeriD· 1 shared

Activity by Year

2024-2024 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 24 mutual co-author links

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1 shared paperBioinformatics

Alberto RomagnoniORCID

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2 papers

Recent·Most cited

BioinformaticsiSciencePeer-reviewedDec 20, 2024

Deep learning uncovers histological patterns of YAP1/TEAD activity related to disease aggressiveness in cancer patients.

Benoît Schmauch, Vincent Cabeli, Omar Darwiche Domingues…·Matteo Cesaroni

This study uses deep learning to predict YAP1/TEAD activity from histology slides, linking histological patterns to disease aggressiveness in cancer patients.

2 citations

humanspatial transcriptomics

𝕏 PostBluesky

PathologyHistopathologyPeer-reviewedJul 14, 2024

Development of a Deep Learning model Tailored for HER2 Detection in Breast Cancer to aid pathologists in interpreting HER2-Low cases

Pierre‐Antoine Bannier, Glenn Broeckx, Loïc Herpin…·Sheeba Irshad

This paper develops a deep learning model to detect HER2 status in breast cancer, showing higher concordance with ground truth than pathologists for HER2-low cases.

17 citations

humanimaging

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