Quick Med Recommendation System using Machine Learning

This paper presents a machine learning-based system that uses sentiment analysis of user-generated drug reviews to provide personalized drug recommendations. A Linear SVC model classifies review sentiments, which are aggregated to rank drugs for specific conditions. A web app enables user interaction, supported by a connected database. Results show improved decision-making and reliability in drug selection.