Author

Vilde Eide Skingen

Oslo University HospitalORCID 0000-0002-1481-2355Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Research Focus:cell type annotation· 1 Approach:deep learning· 1 Organism:human· 1 Assay:imaging· 1

Frequent Co-Authors

Gozde N. GunesliiD· 1 shared Heidi LyngiD· 1 shared Kari-Anne Frikstad Valen· 1 shared Lawrence S. YoungiD· 1 shared Nasir RajpootiD· 1 shared Ruoyu WangiD· 1 shared

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2025-2025 · peak 1/yr

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6 top collaborators · 15 mutual co-author links

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1 shared paperPathology

Gozde N. GunesliORCID

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1 paper

Recent·Most cited

Pathologynpj Precision OncologyPeer-reviewedJan 11, 2025

A Deep Learning Framework for Predicting Prognostically Relevant Consensus Molecular Subtypes in HPV-Positive Cervical Squamous Cell Carcinoma from Routine Histology Images

Ruoyu Wang, Gozde N. Gunesli, Vilde Eide Skingen…·Nasir Rajpoot

This paper develops a deep learning framework to predict consensus molecular subtypes in HPV-positive cervical cancer from histology images, showing significant survival stratification and TME differences between subtypes.

11 citations

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