Author

Xavier Farré

ORCID 0000-0001-8702-4643Unclaimed 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 Assay:imaging· 2 Research Focus:cell type annotation· 1 Research Focus:differential expression· 1 Organism:human· 1 Assay:spatial transcriptomics· 1

Frequent Co-Authors

Anant MadabhushiiD· 2 shared Jonathan T.C. LiuiD· 2 shared Kevin W. BishopiD· 2 shared Lawrence D. TrueiD· 2 shared Michelle R. DownesiD· 2 shared Rui WangiD· 2 shared Andrew H. SongiD· 1 shared David BrenesiD· 1 shared

Activity by Year

2025-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 42 mutual co-author links

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2 shared papersPathology

Anant MadabhushiORCID

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2 papers

Recent·Most cited

Detection of prostate cancer in 3D pathology datasets via generative immunolabeling

Robert Serafin, Jennifer Salguero López, SP Chow, Rui Wang, Yujie Zhao, Elena Baraznenok, Lydia Lan, Kevin W. Bishop, Michelle R. Downes, Xavier Farré, Lawrence D. True, Priti Lal, Anant Madabhushi, Jonathan T.C. Liu

This paper develops a 3D computational pipeline called SIGHT to detect prostate cancer in pathology datasets using generative immunolabeling, achieving an F1 score comparable to pathologist agreement.

Modern Pathology · Feb 14, 2026Peer-reviewedPathology

Deep-learning triage of 3D pathology datasets for comprehensive and efficient pathologist assessments

Gan Gao, Renao Yan, Andrew H. Song, Huai-Ching Hsieh, Lindsey A. Erion Barner, Fiona Wang, David Brenes, Sarah S. L. Chow, Rui Wang, Kevin W. Bishop, Yongjun Liu, Xavier Farré, Mukul K. Divatia, Michelle R. Downes, Funda Vakar‐Lopez, , Jonathan T.C. Liu

CARP3D uses deep learning to prioritize high-risk 2D sections in 3D pathology data, improving disease detection while reducing pathologist workload.

bioRxiv · Jul 20, 2025 · PreprintPathology