Angela Mastronuzzi, Head of Neuro-Oncology Unit at Bambino Gesù Children’s Hospital and President of AIEOP, shared a post on LinkedIn:
“Happy to share on behalf of Ospedale Pediatrico Bambino Gesù team:
“Multi-step artificial intelligence–based model for surgical timing in pediatric oncology”
This study presents a two-phase AI-based model to predict surgical wait times in pediatric oncology patients. Using real-world data from 1,478 patients and 6,145 surgeries, the model first classifies surgical urgency, then estimates wait times for urgent cases. Random Forest emerged as the best-performing algorithm in both phases, and SHAP analysis identified similar key predictive features. Results support AI’s role in improving surgical planning, resource allocation, and clinical decision-making.
This article was published in Italian.”
Title: Multi-step artificial intelligence–based model for surgical timing in pediatric oncology
Authors: Silvia Capuzzi, Federico Baldisseri, Antonella Cacchione, Andrea Carai, Francesco Fabozzi, Antonio Pietrabissa, Angela Mastronuzzi, Alberto Eugenio Tozzi, Diana Ferro
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