Publication

Abstract : Consuming drug is a common action to get relief from a disease. Drugs not only cure a disease, but also create few problems like side effects. Sometimes side effects may be tolerable such as headache which automatically cures after some time, but side effects can become a dangerous health problem like affecting kidney which is irreversible. Side effects are one of the top reasons for failure of a drug to enter the market. There are lots of drugs for a disease. A drug is said to be best, if it cures the disease completely and results in minimal side effects. In this paper we first identify the correct disease for a patient based on symptoms. The symptoms may be both direct physical symptoms and temporal symptoms (which are responsible for a disease only for a time period). Then, we address the problem of recommending the best drug which makes the side effects as minimum as possible. We propose some optimization that reduces time complexity for the recommendation model. To verify the efficiency of our model, we conducted experimental test on benchmark datasets and the results show our algorithm outperforms the existing works.