Evaluation of a Natural Language Processing Model to Identify and Characterize Patients in the United States With High-Risk Non–Muscle-Invasive Bladder Cancer

PURPOSE: Treatment of non–muscle-invasive bladder cancer (NMIBC) is guided by risk stratification using clinical and pathologic criteria. This study aimed to develop a natural language processing (NLP) model for identifying patients with high-risk NMIBC retrospectively from unstructured electronic m...

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Detalles Bibliográficos
Autores principales: Narayan, Vikram M., Siolas, Despina, Meadows, Eric S., Turzhitsky, Vladimir, Sillah, Arthur, Imai, Kentaro, McMurry, Andrew J., Li, Haojie
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Wolters Kluwer Health 2023
Materias:
ORIGINAL REPORTS
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10642898/
https://www.ncbi.nlm.nih.gov/pubmed/37906722
http://dx.doi.org/10.1200/CCI.23.00096

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10642898/
https://www.ncbi.nlm.nih.gov/pubmed/37906722
http://dx.doi.org/10.1200/CCI.23.00096

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