This project focuses on predicting the risk of medicine overdose using machine learning techniques. Medicine overdose is a critical healthcare issue that can lead to severe health complications and even death if not identified early. The proposed system analyzes patient-related data, including dosage, medical history, and other relevant parameters, to identify patterns associated with overdose risks. Various machine learning algorithms are applied to build a predictive model that can classify and detect potential overdose cases with improved accuracy. The system aims to assist healthcare professionals and individuals in making informed decisions, thereby reducing the chances of harmful drug misuse. This project demonstrates the application of data science in healthcare for early risk detection and prevention.
B et al. (2026) studied this question.