Intelligent Clinical Decision Support System for Monitoring and Preventing Adverse Effects of Drug-Drug Interaction

Pharmacovigilance is a crucial practice that aims to record and evaluate the side effects of medications, particularly their frequency and severity. In the current study, we propose an intelligent decision support system that allows pharmacists and patients to detect and prevent unwanted drug interactions. This system uses advanced business intelligence techniques and machine learning approaches to predict the severity of new drug interactions. The intelligent models generated are based on real dataset provided by the pharmacology laboratory of the university hospital establishment of Oran in Algeria and reliable sources. The aim of the proposed system is to improve medication management and provide appropriate recommendations to patients, while providing pharmacists with a user -friendly interface to manage the drug interaction database.