Selección de agrupamiento de genes para la predicción de la supervivencia en pacientes con cáncer de mama

Autores/as

  • Khennedy Bacule dos Santos Instituto de Ciências Matemáticas e de Computação (ICMC), USP - São Carlos
  • Israel Tojal da Silva A.C.Camargo Cancer Center
  • Mariana Cúri Instituto de Ciências Matemáticas e de Computação (ICMC), USP - São Carlos

DOI:

https://doi.org/10.59681/2175-4411.v15.iEspecial.2023.1103

Palabras clave:

Aprendizaje Automático, Cáncer de mama, Expresión génica

Resumen

La estratificación del riesgo basada en datos moleculares para predecir la progresión o el resultado del cáncer es una tarea importante para respaldar la toma de decisiones clínicas en oncología. En este trabajo, usamos el modelo de Cox y K-means para definir una firma basada en la expresión génica de pronóstico. Nuestro enfoque logró un C-index (0,8341) y supera al modelo de Cox utilizando solo datos clínicos (0,6348). En general, esto demuestra que la firma genética encontrada está relacionada con la evolución del estado clínico de la paciente, detectando características moleculares relacionadas con el pronóstico en cáncer de mama.

Biografía del autor/a

Khennedy Bacule dos Santos, Instituto de Ciências Matemáticas e de Computação (ICMC), USP - São Carlos

Instituto de Ciências Matemáticas e de Computação (ICMC), USP - São Carlos, São Paulo (SP), Brasil.

Israel Tojal da Silva, A.C.Camargo Cancer Center

A.C.Camargo Cancer Center, São Paulo (SP), Brasil.

Mariana Cúri, Instituto de Ciências Matemáticas e de Computação (ICMC), USP - São Carlos

Instituto de Ciências Matemáticas e de Computação (ICMC), USP - São Carlos, São Paulo (SP), Brasil.

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Publicado

2023-07-20

Cómo citar

Santos, K. B. dos, Silva, I. T. da, & Cúri, M. (2023). Selección de agrupamiento de genes para la predicción de la supervivencia en pacientes con cáncer de mama. Journal of Health Informatics, 15(Especial). https://doi.org/10.59681/2175-4411.v15.iEspecial.2023.1103

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