Author

Farzaneh Seyedshahi

Cancer Research UK Scotland InstituteORCID 0009-0007-1111-052XUnclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Cancer Biology· 1 Pathology· 1

Signature Assays, Organisms & Methods

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Research Focus:cell type annotation· 2 Approach:deep learning· 2 Organism:human· 2 Assay:imaging· 2

Frequent Co-Authors

John P. C. Le QuesneiD· 2 shared Ke YuaniD· 2 shared Adalberto Claudio QuirosiD· 1 shared Ana TeodòsioiD· 1 shared Apostolos NakasiD· 1 shared Arnaud ScherpereeliD· 1 shared Catherine FickeniD· 1 shared Cathy J. RichardsiD· 1 shared

Activity by Year

2025-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 38 mutual co-author links

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2 shared papersCancer Biology

John P. C. Le QuesneORCID

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2 papers

Recent·Most cited

Cancer BiologybioRxivPreprintSep 10, 2026

Self-Supervised AI Discovery of Histomorphological Phenotypes from Routine Mesothelioma Biopsies

Farzaneh Seyedshahi, Francesca Damiola, Ruth Sequeiros…·John P. C. Le Quesne

This paper uses self-supervised learning to discover histomorphological phenotypes from mesothelioma biopsies, linking tissue patterns to molecular and clinical outcomes.

DOI 10.64898/2026.08.09.743741

humanimaging

𝕏 PostBluesky

PathologyNature CommunicationsPeer-reviewedOct 7, 2025

A histomorphological atlas of resected mesothelioma discovered by self-supervised learning from 3446 whole-slide images

Farzaneh Seyedshahi, Kai Rakovic, Nicolas Poulain…·John P. C. Le Quesne

This paper uses self-supervised learning on 3446 H&E-stained mesothelioma slides to create a histomorphological atlas, achieving high predictive performance and revealing molecular insights.

2 citations

humanimaging

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