In today’s digital era healthcare is one among the major core areas of the medical domain. People trying to find suitable health-related information that they are concerned with. The Internet could be a great resource for this kind of data, however you need to take care to avoid getting harmful information. Nowadays, a colossal quantity of clinical information dispersed totally across different websites on the Internet prevents users from finding useful information for their well-being improvement. Errors in medication are one of the foremost severe medical faults that would be a threat to patients’ lives. These problems increases the requirement to use recommendation systems within the domain of healthcare to assist users create additional economical and correct health-related decisions. During this paper, drug recommendation systems are developed to help end-users in distinctive correct medications for a particular wellness based on the reviews of other end-users provided on totally different medications for various specific diseases. The goal of this recommendation system is to examine the dataset using data mining concepts, visualization, sentiment analysis and recommend drugs based on the condition, ratings and reviews using Machine Learning approaches, Content and Collaborative filtering approach, for each health condition of a patient.
Mohapatra, Mahima; Nayak, Mamata; and Mahapatra, Saswati
"A Machine Learning based Drug Recommendation System for Health Care,"
Graduate Research in Engineering and Technology (GRET): Vol. 1:
6, Article 2.
Available at: https://www.interscience.in/gret/vol1/iss6/2