The role of decision tree and machine learning models for outcome prediction of bupropion exposure: A nationwide analysis of more than 14 000 patients in the United States.

Abstract	Bupropion is widely used for the treatment of major depressive disorder and for smoking cessation assistance. Unfortunately, there are no practical systems to assist clinicians or poison centres in predicting outcomes based on clinical features. Hence, the purpose of this study was to use a decision tree approach to inform early diagnosis of outcomes secondary to bupropion overdose. This study utilized a dataset from the National Poison Data System, a 6-year retrospective cohort study on toxic exposures and patient outcomes. A machine learning algorithm (decision tree) was applied to the dataset using the sci-kit-learn library in Python. Shapley Additive exPlanations (SHAP) were used as an explainable method. Comparative analysis was performed using random forest (RF), Gradient Boosting classification, eXtreme Gradient Boosting, Light Gradient Boosting (LGM) and voting ensembling. ROC curve and precision-recall curve were used to analyse the performance of each model. LGM and RF demonstrated the highest performance to predict outcome of bupropion exposure. Multiple seizures, conduction disturbance, intentional exposure, and confusion were the most influential factors to predict the outcome of bupropion exposure. Coma and seizure, including single, multiple and status, were the most important factors to predict major outcomes.
Authors	Omid Mehrpour, Farhad Saeedi, Varun Vohra, Jafar Abdollahi, Farshad M Shirazi, Foster Goss
Journal	Basic & clinical pharmacology & toxicology (Basic Clin Pharmacol Toxicol) Vol. 133 Issue 1 Pg. 98-110 (Jul 2023) ISSN: 1742-7843 [Electronic] England
PMID	36960587 (Publication Type: Journal Article)
Copyright	© 2023 Nordic Association for the Publication of BCPT (former Nordic Pharmacological Society). Published by John Wiley & Sons Ltd.
Chemical References	Bupropion
Topics	Humans United States (epidemiology) Bupropion Depressive Disorder, Major (drug therapy, epidemiology) Retrospective Studies Seizures Machine Learning Decision Trees

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