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Updated: Jan 8, 2026

Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma

Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma

Published on: October 10, 2018

Desarrollo y validación de herramientas de aprendizaje automático para predecir complicaciones postoperatorias en la

Ottavia Cicerone^1,2, Simone Frassini^1,2, Anna Gallotti³

¹Dipartimento di scienze clinico-chirurgiche, diagnostiche e pediatriche, University of Pavia, Pavia, Italy.

Updates in surgery

|December 19, 2025

Resumen

Los modelos de aprendizaje automático predicen complicaciones postoperatorias en la colecistitis aguda calculosa (CAC). CholeSurgRisk I (preoperatorio) y CholeSurgRisk II (integral) ofrecen una estratificación de riesgos mejorada para mejores resultados en los pacientes.

Palabras clave:

colecistitis aguda colecistectomía laparoscópica complicaciones postoperatorias aprendizaje automático predicción de riesgos

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