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Modello multi-step basato su intelligenza artificiale per il timing chirurgico in oncologia pediatrica
0
Zitationen
9
Autoren
2025
Jahr
Abstract
This study presents a two-phase AI-based model to predict surgical wait times in paediatric oncology patients. Using real-world data from 1478 patients and 6145 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.
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