Author

N. A. Cipriani

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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Research Focus:cell type annotation· 2 Organism:human· 2 Assay:bulk RNA-seq· 1 Research Focus:clustering· 1 Approach:deep learning· 1 Research Focus:differential expression· 1 Assay:imaging· 1 Approach:machine learning (classical)· 1

Frequent Co-Authors

A. T. Pearson· 2 shared J. Dolezal· 2 shared J. N. Kather· 2 shared S. Kochanny· 2 shared A. Srisuwananukorn· 1 shared C. Loeffler· 1 shared C. Trautwein· 1 shared C. Wang· 1 shared

Activity by Year

2019-2023 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 37 mutual co-author links

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2 shared papersCancer Biology

A. T. Pearson

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Author profile →

2 papers

Recent·Most cited

Latent transcriptional programs reveal histology-encoded tumor features spanning tissue origins

H. M. Hieromnimon, J. Dolezal, K. Doytcheva, F. M. Howard, S. Kochanny, Z. Zhang, R. L. Grossman, K. Tanager, C. Wang, J. N. Kather, E. Izumchenko, N. A. Cipriani, E. J. Fertig, A. T. Pearson, S. J. Riesenfeld

This paper uses machine learning to identify latent transcriptional programs in squamous cell carcinomas from histology images, linking them to clinically relevant biological processes.

bioRxiv · Mar 22, 2023Cancer Biology

Deep learning detects virus presence in cancer histology

J. N. Kather, J. Schulte, H. I. Grabsch, C. Loeffler, H. S. Muti, J. Dolezal, A. Srisuwananukorn, N. Agrawal, S. Kochanny, S. von Stillfried, P. Boor, T. Yoshikawa, D. Jaeger, C. Trautwein, P. Bankhead, , A. T. Pearson

This paper uses deep learning to detect the presence of HPV and EBV in cancer histology images, achieving high accuracy in predicting virus-associated tumors.

bioRxiv · Jul 5, 2019 · PreprintCancer Biology