Classification of retinoblastoma-1 gene mutation with machine learning-based models in bladder cancer

PURPOSE: This study aims to evaluate the potential of machine learning algorithms built with radiomics features from computed tomography urography (CTU) images that classify RB1 gene mutation status in bladder cancer. METHOD: The study enrolled CTU images of 18 patients with and 54 without RB1 mutat...

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Detalles Bibliográficos
Autores principales: İnce, Okan, Yıldız, Hülya, Kisbet, Tanju, Ertürk, Şükrü Mehmet, Önder, Hakan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9061624/
https://www.ncbi.nlm.nih.gov/pubmed/35520623
http://dx.doi.org/10.1016/j.heliyon.2022.e09311

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9061624/
https://www.ncbi.nlm.nih.gov/pubmed/35520623
http://dx.doi.org/10.1016/j.heliyon.2022.e09311

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