Machine learning feasibility study for anesthesia induction parameter prediction using multi-stage CatBoost models. Integrates pharmacogenomics, patient demographics, and clinical data with SHAP explainability for personalized anesthesia type selection, dosage calculation, and response prediction.
machine-learning supervised-learning hyperparameter-optimization classification ensemble-learning gradient-boosting catboost multi-stage-modeling
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Updated
Sep 29, 2025 - Jupyter Notebook