Quantitative characterization of eosinophilia in nasal polyps with AI-based single cell classification

Martin Stampe; Ida Skovgaard Christiansen; Vibeke Backer; Kasper Aanæs; Anne Sophie Homøe; Jens Tidemandsen; Emilie Neumann Nielsen; Sigrid Louise Hjorth Rasmussen; Rasmus Hartvig; Katalin Kiss; Thomas Hartvig Lindkær Jensen

doi:10.1002/alr.23454

Quantitative characterization of eosinophilia in nasal polyps with AI-based single cell classification

Martin Stampe^*, Ida Skovgaard Christiansen, Vibeke Backer, Kasper Aanæs, Anne Sophie Homøe, Jens Tidemandsen, Emilie Neumann Nielsen, Sigrid Louise Hjorth Rasmussen, Rasmus Hartvig, Katalin Kiss, Thomas Hartvig Lindkær Jensen

^*Corresponding author

Institut for Naturvidenskab og Miljø

Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › peer review

Abstract

Key Points: Eosinophilic granulocytes have characteristic morphological features. This makes them prime candidates for utilization of a single cell binary classification network. Single cell binary classification networks can reliably help quantify eosinophils in nasal polyps.

Originalsprog	Engelsk
Tidsskrift	International Forum of Allergy and Rhinology
Vol/bind	15
Udgave nummer	2
Sider (fra-til)	188-190
Antal sider	3
ISSN	2042-6976
DOI	https://doi.org/10.1002/alr.23454
Status	Udgivet - feb. 2025

Emneord

Chronic rhinosinustis
Disease severity
Eosinophilic rhinitis
Nasal polyposis

Link til dokument

10.1002/alr.23454Licens: CC BY-NC-ND

Quantitative characterization of eosinophilia in nasal polyps with AI-based single cell classificationForlagets udgivne version, 267 KBLicens: CC BY-NC-ND

Citer dette

Stampe, M., Christiansen, I. S., Backer, V., Aanæs, K., Homøe, A. S., Tidemandsen, J., Nielsen, E. N., Rasmussen, S. L. H., Hartvig, R., Kiss, K., & Jensen, T. H. L. (2025). Quantitative characterization of eosinophilia in nasal polyps with AI-based single cell classification. International Forum of Allergy and Rhinology, 15(2), 188-190. https://doi.org/10.1002/alr.23454

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abstract = "Key Points: Eosinophilic granulocytes have characteristic morphological features. This makes them prime candidates for utilization of a single cell binary classification network. Single cell binary classification networks can reliably help quantify eosinophils in nasal polyps.",

keywords = "Chronic rhinosinustis, Disease severity, Eosinophilic rhinitis, Nasal polyposis, Chronic rhinosinustis, Disease severity, Eosinophilic rhinitis, Nasal polyposis",

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AU - Christiansen, Ida Skovgaard

AU - Backer, Vibeke

AU - Aanæs, Kasper

AU - Homøe, Anne Sophie

AU - Tidemandsen, Jens

AU - Nielsen, Emilie Neumann

AU - Rasmussen, Sigrid Louise Hjorth

AU - Hartvig, Rasmus

AU - Kiss, Katalin

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KW - Disease severity

KW - Eosinophilic rhinitis

KW - Nasal polyposis

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KW - Disease severity

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KW - Nasal polyposis

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