Drug Recommendation System based on Sentiment Analysis of Drug Reviews using Machine Learning

• Python
• Machine Learning

With the number of corona virus cases growing exponentially, the nations are facing a shortage of doctors, particularly in rural areas where the quantity of specialists is less compared to urban areas. A doctor takes roughly 6 to 12 years to procure the necessary qualifications. Thus, the number of doctors can?t be expanded quickly in a short time frame. A Telemedicine framework ought to be energized as far as possible in this difficult time. Over 40% medicine, specialists make mistakes while prescribing since specialists compose the solution as referenced by their knowledge, which is very restricted. Choosing the top-level medication is significant for patients who need specialists that know wide-based information about microscopic organisms, antibacterial medications, and patients. . In the drug recommender system, medicine is offered on a specific condition dependent on patient reviews using sentiment analysis and feature engineering. Sentiment analysis is a progression of strategies, methods, and tools for distinguishing and extracting emotional data, such as opinion and attitudes, from language. On the other hand, Featuring engineering is the process of making more features from the existing ones; it improves the performance of models.