Author

Nicholas H. Smith

Stanford MedicinePrimary ORCID profile (0009-0008-0026-0757 · 4 papers)Unclaimed ORCID profile · follow to get notified of new preprints

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Same name, identified by ORCID

Nicholas H. SmithiD4 papers · Technical University of Munich

Biology Disciplines

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Cancer Biology· 1

Signature Assays, Organisms & Methods

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Research Focus:cell type annotation· 1 Approach:contrastive learning· 1 Approach:deep learning· 1 Research Focus:differential expression· 1 Research Focus:drug response / drug discovery· 1 Research Focus:gene regulatory network inference· 1 Organism:human· 1 Assay:imaging· 1

Frequent Co-Authors

Allison MeisneriD· 1 shared Brennan Geti SimoniD· 1 shared Cansu KarakaşiD· 1 shared Christina N. CurtisiD· 1 shared Clemens L. WeißiD· 1 shared Corey Wayne SpeersiD· 1 shared Darren ChaniD· 1 shared Gregory R. BeaniD· 1 shared

Activity by Year

2025-2025 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

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1 shared paperCancer Biology

Allison MeisnerORCID

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Author profile →

1 paper

Recent·Most cited

Generative AI Enables Breast Cancer Genomic Subtype Prediction from Histology Images

Brennan Geti Simon, Clemens L. Weiß, Darren Chan, Lise Mangiante, Zhicheng Ma, Nicholas H. Smith, Allison Meisner, James Michael Rae, Corey Wayne Speers, Kathy S. Albain, Cansu Karakaş, Gregory R. Bean, Silvana Andrea Mouron, Miguel Quintela-Fandiño, Christina N. Curtis

PATH-IC uses generative AI to predict breast cancer genomic subtypes from histology images, achieving high accuracy and correlating with clinical outcomes.

bioRxiv · Dec 29, 2025 · PreprintCancer Biology