Author

M. van Rijthoven

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Pathology· 1

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

F. Ciompi· 1 shared F. Pagliarulo· 1 shared H. Moch· 1 shared J. van der Laak· 1 shared K. Silina· 1 shared M. van den Broek· 1 shared P. Schraml· 1 shared S. Obahor· 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

F. Ciompi

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1 paper

Recent·Most cited

Multi-resolution deep learning characterizestertiary lymphoid structures in solid tumors

M. van Rijthoven, S. Obahor, F. Pagliarulo, M. van den Broek, P. Schraml, H. Moch, J. van der Laak, F. Ciompi, K. 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.

bioRxiv · Apr 3, 2023Pathology