Drugs Rating Generation and Recommendation from Sentiment Analysis of Drug Reviews using Machine Learning

Abstract

As a result of all of this complex information, the user can benefit from a recommendation system by forming an awareness of their needs and making well-informed judgments. User-generated material is portrayed using human language in a variety of ways, making it difficult to make recommendations based on sentiment analysis. Health and medicine have received much too little attention in research, which has tended to concentrate on more mundane topics like product reviews for electronics, movies, and dining establishments. To improve public health and make the right decision, it may be necessary to do a sentiment analysis of healthcare in general and the drug experiences of individuals in particular. Design and implementation of a drug recommendation system that uses sentiment analysis technologies on drug reviews are presented in this study. The goal of this study is to create a decision-support platform that will assist patients in making more informed decisions about their pharmacological treatment options.