Author

Nicole A. Cipriani

University of ChicagoORCID 0000-0003-3092-2746Unclaimed 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:benchmarking· 1 Research Focus:cell-cell communication· 1 Research Focus:differential expression· 1 Research Focus:gene regulatory network inference· 1 Assay:imaging· 1 Assay:spatial transcriptomics· 1

Frequent Co-Authors

Alexander T. PearsoniD· 2 shared Jakob Nikolas KatheriD· 2 shared Jefree J. SchulteiD· 2 shared Lara Rosaline HeijiD· 2 shared Sara E. KochannyiD· 2 shared Akash PatnaikiD· 1 shared Amelie EchleiD· 1 shared Andrew M. Hanby· 1 shared

Activity by Year

2020-2021 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

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2 shared papersBioinformatics

Alexander T. PearsonORCID

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2 papers

Recent·Most cited

BioinformaticsNature CommunicationsPeer-reviewedJul 20, 2021

The Impact of Digital Histopathology Batch Effect on Deep Learning Model Accuracy and Bias

Frederick Matthew Howard, James M. Dolezal, Sara E. Kochanny…·Alexander T. Pearson

This paper shows that digital histopathology batch effects in TCGA data affect DL model accuracy and bias, and proposes a method to address this issue.

330 citationstop 1%

humanspatial transcriptomics

𝕏 PostBluesky

GeneticsNature CancerPeer-reviewedJul 27, 2020

Pan-cancer image-based detection of clinically actionable genetic alterations

Jakob Nikolas Kather, Lara Rosaline Heij, Heike Irmgard Grabsch…·Tom Luedde

This paper develops a deep learning method to predict genetic alterations from histological images across multiple cancer types.

670 citationstop 1%

humanimaging

𝕏 PostBluesky