Author

Kirsten Damgaard Hoff

Agilent Technologies (Denmark)

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Pathology· 1

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

Amir Ben‐Dor· 1 shared Anya Tsalenko· 1 shared Daniela Rabkin· 1 shared Elad Arbel· 1 shared Frederik Aidt· 1 shared Gitte Nielsen· 1 shared Itay RemeriD· 1 shared Jens MollerupiD· 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 paperPathology

Amir Ben‐Dor

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1 paper

Recent·Most cited

Quantification of HER2-low and ultra-low expression in breast cancer specimens by quantitative IHC and artificial intelligence

Frederik Aidt, Elad Arbel, Itay Remer, Oded Ben-David, Amir Ben‐Dor, Daniela Rabkin, Kirsten Damgaard Hoff, Karin Salomon, Sarit Aviel‐Ronen, Gitte Nielsen, Jens Mollerup, Lars Jacobsen, Anya Tsalenko

This paper develops qIHC and AI-based methods to quantify HER2 expression in breast cancer, showing significant differences between IHC categories and high spatial heterogeneity.

Journal of Pathology Informatics · Aug 26, 2025Peer-reviewedPathology