Work

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

Year: 2024

Type: article

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.

Source: International Forum of Allergy & Rhinology

DOI: 10.1002/alr.23454

Authors: 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

Institutions: Rigshospitalet, Roskilde University, University of Copenhagen

Language: English

Topic: Sinusitis and nasal conditions

Subfield: Otorhinolaryngology

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: hybrid

Estimated APC paid: $3,900

OpenAlex ID: W4402678792

FWCI: 1.15

Cites: 7

Cited by: 3

Related to: 10