DRUG RECOMMENDATION SYSTEM BASED ON SENTIMENT ANALYSIS OF DRUG REVIEWS USING MACHINE LEARNING

Abstract

Since coronavirus has shown up, inaccessibility of legitimate clinical resources is
at its peak, like the shortage of specialists and healthcare workers, lack of proper
equipment and medicines etc. Due to unavailability, individuals started taking
medication independently without appropriate consultation, making the health
condition worse than usual. This Application intends to present a drug recommender
system that can drastically reduce specialists heap. In this project, we build a medicine
recommendation system that uses patient reviews to predict the sentiment using
various vectorization processes, which can help recommend the top drug for a given
disease by different classification algorithms. The results show that MLP classifier
outperforms all other models with high accuracy.