Drug Recommendation based on Sentiment Analysis using ML

Drug Recommendation based on Sentiment Analysis using ML

Dr.Krishnareddy K R1, Dr. Aravinda T V2, Kumarswamy H3  , Ramesh B E4  , Avinash G M5 ,

M R Desai6, Vishwas C N7

1Professor, Department of Computer Science and Engineering S.J.M.I.T. Chitradurga, Karnataka

2Professor, Department of Computer Science and Engineering S.J.M.I.T. Chitradurga, Karnataka

3Assistant Professor, Department of Computer Science and Engineering S.J.M.I.T. Chitradurga, Karnataka

4Associate Professor, Department of Computer Science and Engineering S.J.M.I.T. Chitradurga, Karnataka

5Assistant Professor, Department of Computer Science and Engineering S.J.M.I.T. Chitradurga, Karnataka

6Assistant Professor, Department of Computer Science and Engineering S.J.M.I.T. Chitradurga, Karnataka

7Student, IVth Sem Mtech, Department of Computer Science and Engineering S.J.M.I.T. Chitradurga, Karnataka

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Abstract - As e-commerce has grown, an increasing number of consumers prefer to buy drugs online for convenience's sake. As a result, the difficulties with health and medical diagnostics are becoming more well known. Because medical professionals write prescriptions based on their very limited experience, they frequently make drug mistakes. Technologies like data mining or recommender systems offer opportunities to investigate potential insight from diagnosis background records and aid physicians in reliably prescribing medications to reduce medication mistake. This effort aims to propose a medication recommendation system that can significantly lessen the workload of professionals. We create a system that, using ML classification algorithms, predicts whether a medicine can be taken or not based on the reviews.

Key Words:  Stress, Machine learning and IT professionals.