Smart Medicare Chatbot Using Dialogflow and Support Vector Machine Algorithm

Chatbots or conversational user interfaces present a new way for individuals to interact with computer systems for assistance. A chatbot allows a user to simply ask questions in the same manner that they would address a human and it responds similarly. The technology at the core of the rise of chatbots is natural language processing (NLP). In medical domain, chatbots can perform prediction tasks which is possible today with advancements in AI, ML and Data Mining Techniques. As in today’s world, the number of patients is increasing rapidly on daily basis with the change in lifestyle. Healthcare services face a huge challenge of supply-and-demand which can be fixed by creating chatbots. These platforms are very much necessary in order to automate medical consultations with or without the presence of a doctor accurately. Chatbots can be made using various tools such as Dialogflow, Microsoft Bot Framework, Telegram Bot API etc. Disease prediction can be done using algorithms such as KNN, CNN, ANN, SVM, Naïve Bayes, Decision tree etc. along with their respective domain specific datasets. Both can be integrated to build a conversational system to predict diseases efficiently. Keywords: Chatbot, healthcare services, supply and demand, automate, disease prediction, Dialogflow, SVM.