Author

Simon Obahor

ORCID 0000-0001-9144-6435Unclaimed 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:cell type annotation· 1 Research Focus:cell-cell communication· 1 Research Focus:clustering· 1 Approach:deep learning· 1 Research Focus:differential expression· 1 Organism:human· 1 Assay:imaging· 1

Frequent Co-Authors

Fabio Pagliarulo· 1 shared Francesco Ciompi· 1 shared Holger MochiD· 1 shared Jeroen van der LaakiD· 1 shared Karina SilinaiD· 1 shared Maries van den BroekiD· 1 shared Mart van RijthoveniD· 1 shared Peter SchramliD· 1 shared

Activity by Year

2023-2023 · peak 1/yr

Co-Author Collaboration Network

8 top collaborators · 28 mutual co-author links

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1 shared paperPathology

Fabio Pagliarulo

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1 paper

Recent·Most cited

PathologybioRxivApr 3, 2023

Multi-resolution deep learning characterizestertiary lymphoid structures in solid tumors

Mart van Rijthoven, Simon Obahor, Fabio Pagliarulo…·Karina Silina

This paper introduces HookNet-TLS, a deep learning model for automated TLS quantification in cancer pathology slides, achieving human-level performance and prognostic associations.

DOI 10.1038/s43856-023-00421-7

humanimaging

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