Artificial intelligence algorithm for neoplastic cell percentage estimation and its application to copy number variation in urinary tract cancer

• Egile Nagusiak: Jinahn Jeong (Egilea), Deokhoon Kim (Egilea), Yeon-Mi Ryu (Egilea), Ja-Min Park (Egilea), Sun Young Yoon (Egilea), Bokyung Ahn (Egilea), Gi Hwan Kim (Egilea), Se Un Jeong (Egilea), Hyun-Jung Sung (Egilea), Yong Il Lee (Egilea), Sang-Yeob Kim (Egilea), Yong Mee Cho (Egilea)
• Formatua: Liburua
• Argitaratua: Korean Society of Pathologists & the Korean Society for Cytopathology, 2024-09-01T00:00:00Z.
• Gaiak: article
• Sarrera elektronikoa: Connect to this object online.

Background Bladder cancer is characterized by frequent mutations, which provide potential therapeutic targets for most patients. The effectiveness of emerging personalized therapies depends on an accurate molecular diagnosis, for which the accurate estimation of the neoplastic cell percentage (NCP)...