Personalized medicine recommendation system

Abstract

Development of Technology has undoubtedly made an incredible impact in the field of medicine. Artificial Intelligence and data science play important roles in developing these healthcare sector based applications in order to provide more efficient and accurate service for the patient. Worldwide, people tend to look for more computer-based solutions for their medicine related scenarios specially when it comes to prescription as the rate of human errors that can happen from a computer bases system is very less as well as it consumes less time. In this modern era, the medical sector is more patient centered system. Therefore, patient’s experiences have major influence on healthcare specially on drug domain. With the expansion of usage of social media, opinion extraction has been widely used to help the current prescribing process by analyzing the opinions of patient’s satisfaction in order to prescribe the most suitable medicine. The proposed system focusses on applying natural language processing techniques and machine learning techniques on reviews of patients related to drug domain and provide suitable recommendation of medicines for each person considering their age, gender, condition and other interact drugs.