Medinsights: Twitter Based Platform for Health Care Analytics

Twitter is a social media platform where the tweets convey opinions, but the interpretation of this unstructured data can be very time-consuming. Medinsights is a data science platform which leverages machine learning and natural language processing technologies on twitter data. This platform helps to analyze the inherent value of the data extracted from tweets such as diseases, treatments, symptoms linked to healthcare domain, which can only be fully exploited through deep data analytics. Medinsights takes particular health-related query on medicine, disease, brand, medical hashtags as input and converts corresponding twitter data into actionable information in order to gain insights and provide diverse recommendations. Medinsights analyses the sentiment, trend, prevalent location to provide meaningful inferences. Medinsights extracts and proposes associated symptoms, diseases, treatments, drugs and brands based on user query from tweets. For this study gradient boosting classifier is used for tweets classification into medical and non medical domain. Word2vec word embeddings with feed forward neural network is used for sentiment analysis. Conditional random field (CRF) is used to extract medical entities from tweets. Medinsights can be helpful to research correlation from tweets and analytics related to healthcare domain.