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Clasificación de tumores renales agresivos y malignos basada en aprendizaje automático a partir de datos multimodales

Mehrnegar Aminy¹, Tejal Gala², Agnimitra Dasgupta¹

¹Department of Aerospace and Mechanical Engineering, Viterbi School of Engineering, University of Southern California (USC), Los Angeles, California, United States of America.

PLOS digital health

|February 20, 2026

Resumen

El aprendizaje automático clasifica con precisión los tumores renales utilizando tomografías computarizadas y datos clínicos, distinguiendo los tipos agresivos de los indolentes. El tamaño del tumor mejoró significativamente la clasificación, ayudando a las estrategias de tratamiento personalizadas.

Palabras clave:

aprendizaje automático tumores renales tomografía computarizada datos clínicos estratificación del riesgo tratamiento personalizado

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