Main Article Content
Abstract
The research aims at Recommending Appropriate Medicine by analysing review of it and mapping it with patient’s condition. After consuming any medicine patients experience certain effects which are both positive and negative. These effects when put forward as reviews about the medicine are helpful in recommending the correct medicine for a particular condition. The review contains the side effects, positive effects and details about how impactful the medicine was to the patient. Usually, for not so serious conditions medicines are recommended according to the previous experience of a person in family or domain knowledge of the pharmacist or few generic conditions, medicines are suggested as per knowledge of the patient. One such example is Crocin, Combiflam for viral. But these medicines are not highly impactful for specific conditions. So in this research we will be using the patient’s reviews to correctly map any medicine with the patient’s condition and using this further recommend an appropriate medicine to the patient. This will also work as an assistant to emerging doctors, pharmacist. In order to do so techniques like text analytics will be used. For accurate recommendation, every word in the review will be analysed to find accurate sentiment of the word.