A cost-effective, machine learning-based new unified risk-classification score (NU-CATS) for patients with endometrial cancer.

Zheng, Shuhua; Wu, Yilin; Donnelly, Eric D; Strauss, Jonathan B

Zheng, Shuhua; Wu, Yilin; Donnelly, Eric D; Strauss, Jonathan B.

Afiliación

Zheng S; Department of Radiation Oncology, Robert H. Lurie Comprehensive Cancer Center of Northwestern University, Chicago, IL 60611, United States of America.
Wu Y; Department of Mathematics, DigiPen Institute of Technology, Redmond, WA 98052, United States of America.
Donnelly ED; Department of Radiation Oncology, Robert H. Lurie Comprehensive Cancer Center of Northwestern University, Chicago, IL 60611, United States of America.
Strauss JB; Department of Radiation Oncology, Robert H. Lurie Comprehensive Cancer Center of Northwestern University, Chicago, IL 60611, United States of America. Electronic address: jonathan.strauss@nm.org.

Gynecol Oncol ; 175: 97-106, 2023 08.

Article en En | MEDLINE | ID: mdl-37336081

Asunto(s)

Neoplasias Endometriales; Humanos; Femenino; Análisis Costo-Beneficio; Neoplasias Endometriales/patología; Pronóstico; Factores de Riesgo; Mutación; Progresión de la Enfermedad

Palabras clave

Biomarkers; Black or African American; Endometrial cancer; Machine learning; Race

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Neoplasias Endometriales Tipo de estudio: Etiology_studies / Health_economic_evaluation / Prognostic_studies / Risk_factors_studies Límite: Female / Humans Idioma: En Revista: Gynecol Oncol Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Estados Unidos

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