Author

K. J. Hewitt

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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Cancer Biology· 2

Signature Assays, Organisms & Methods

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Approach:deep learning· 2 Assay:imaging· 2 Research Focus:benchmarking· 1 Research Focus:cell type annotation· 1 Research Focus:differential expression· 1 Research Focus:gene regulatory network inference· 1 Organism:human· 1 Research Focus:variant calling· 1

Frequent Co-Authors

C. M. L. Loeffler· 2 shared D. Cifci· 2 shared J. N. Kather· 2 shared M. van Treeck· 2 shared O. L. Saldanha· 2 shared T. P. Seraphin· 2 shared A. Echle· 1 shared A. T. Pearson· 1 shared

Activity by Year

2021-2022 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 42 mutual co-author links

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2 shared papersCancer Biology

C. M. L. Loeffler

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2 papers

Recent·Most cited

Cancer BiologybioRxivPreprintSep 15, 2022

Self-supervised deep learning for pan-cancer mutation prediction from histopathology

O. L. Saldanha, C. M. L. Loeffler, J. M. Niehues…·J. N. Kather

This paper develops a self-supervised deep learning pipeline to predict genetic mutations from histopathology images across seven cancer types in two large datasets.

DOI 10.1101/2022.09.15.507455

humanimaging

𝕏 PostBluesky

Cancer BiologybioRxivPreprintDec 19, 2021

DeepMed: A unified, modular pipeline for end-to-end deep learning in computational pathology

M. van Treeck, D. Cifci, N. Ghaffari Laleh…·J. N. Kather

DeepMed provides a modular, scalable AI pipeline for predicting molecular and histopathological features from histopathology images, with public benchmark data.

DOI 10.1101/2021.12.19.473344

imagingdeep learning

𝕏 PostBluesky