Machine Learning of Urine Cytology Highlights Increased Neutrophil Count in Muscle-Invasive Urothelial Carcinoma

Objective: This study conducted an unsupervised learning cluster analysis on urine cytological images of high-grade urothelial carcinoma to assess their explanatory potential. Materials and Methods: A total of 124 urine cytology specimens of urothelial carcinoma, collected between December 2010 to D...

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Autors principals:	Moe Kameda, Sayaka Kobayashi, Yoshimi Nishijima, Ryosuke Akuzawa, Rio Kaneko, Rio Shibanuma, Seiji Arai, Hayato Ikota, Kazuhiro Suzuki, Hideaki Yokoo, Masanao Saio
Format:	Artigo
Idioma:	Inglês
Publicat:	Wolters Kluwer Medknow Publications 2025-07-01
Col·lecció:	Journal of Cytology
Matèries:	explainable ai machine learning t-distributed stochastic neighbor embedding (t-sne) urine cytology urothelial carcinoma
Accés en línia:	https://doi.org/10.4103/joc.joc_158_24
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