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

IF 7.2 2区 医学 Q1 OTORHINOLARYNGOLOGY
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
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引用次数: 0

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.

利用基于人工智能的单细胞分类对鼻息肉中的嗜酸性粒细胞进行定量表征。
要点嗜酸性粒细胞具有特征性的形态特征。这使它们成为利用单细胞二元分类网络的主要候选者。单细胞二元分类网络能可靠地帮助量化鼻息肉中的嗜酸性粒细胞。
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来源期刊
CiteScore
11.70
自引率
10.90%
发文量
185
审稿时长
6-12 weeks
期刊介绍: International Forum of Allergy & Rhinologyis a peer-reviewed scientific journal, and the Official Journal of the American Rhinologic Society and the American Academy of Otolaryngic Allergy. International Forum of Allergy Rhinology provides a forum for clinical researchers, basic scientists, clinicians, and others to publish original research and explore controversies in the medical and surgical treatment of patients with otolaryngic allergy, rhinologic, and skull base conditions. The application of current research to the management of otolaryngic allergy, rhinologic, and skull base diseases and the need for further investigation will be highlighted.
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