基于人工智能的单细胞分类对鼻息肉中嗜酸性粒细胞增多症的定量表征
Quantitative characterization of eosinophilia in nasal polyps with AI-based single cell classification.
作者信息
Stampe Martin, Christiansen Ida Skovgaard, Backer Vibeke, Aanæs Kasper, Homøe Anne-Sophie, Tidemandsen Jens, Nielsen Emilie Neumann, Rasmussen Sigrid Louise Hjorth, Hartvig Rasmus, Kiss Katalin, Jensen Thomas Hartvig Lindkær
机构信息
Department of Pathology, Rigshospitalet, Copenhagen, Denmark.
Department of Head and Neck Surgery, Hovedortocentret, Rigshospitalet, Copenhagen, Denmark.
出版信息
Int Forum Allergy Rhinol. 2025 Feb;15(2):188-190. doi: 10.1002/alr.23454. Epub 2024 Sep 20.
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.
嗜酸性粒细胞具有特征性的形态学特征。这使其成为利用单细胞二元分类网络的主要候选对象。单细胞二元分类网络能够可靠地帮助量化鼻息肉中的嗜酸性粒细胞。
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