Predictive models of response to neoadjuvant chemotherapy in muscle-invasive bladder cancer using nuclear morphology and tissue architecture

Characterizing likelihood of response to neoadjuvant chemotherapy (NAC) in muscle-invasive bladder cancer (MIBC) is an important yet unmet challenge. In this study, a machine-learning framework is developed using imaging of biopsy pathology specimens to generate models of likelihood of NAC response....

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Detalles Bibliográficos
Autores principales: Mi, Haoyang, Bivalacqua, Trinity J., Kates, Max, Seiler, Roland, Black, Peter C., Popel, Aleksander S., Baras, Alexander S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8484511/
https://www.ncbi.nlm.nih.gov/pubmed/34622225
http://dx.doi.org/10.1016/j.xcrm.2021.100382

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8484511/
https://www.ncbi.nlm.nih.gov/pubmed/34622225
http://dx.doi.org/10.1016/j.xcrm.2021.100382

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