Disease Detection Using RASA Chatbot

Chatbots, or conversational AI(Artificial Intelligence) Interfaces, provide individuals a new way to interact with computer systems. Chatbots allow users to have conversations with the system by asking questions in the way that they would with another human beings. The current adoption rate of chatbots on computer chat platforms is very high. Such robots use artificial intelligence to understand human input and respond accordingly. The core technology for the rise of chatbots is “Natural language processing” (NLP). The recent advancements in NLP have allowed chatbots to be more receptive than ever. Today, humans can interact with the chatbot systems anytime, anywhere. Chatbots can perform predictive tasks (especially in the medical field), which is now possible with advances in artificial intelligence and data mining technology. Healthcare, agriculture and education are important areas that need the most attention. In today’s world, with the change in lifestyle and the current pandemic, illnesses have increased in the general population. As a result, the need for hospitals and doctors have increased substantially. Patients have to spend their time waiting to be taken care of by the doctors. Also, doctors have an immense amount of workload with the amount of visits they have. Thus, the future of healthcare depends on the ability of care providers to perform accurate remote diagnosis. This can be done by collecting data remotely, and by using artificial intelligence to analyse data to improve business and health outcomes. In this paper we analysed datasets to accurately detect diseases with classification techniques such as SVM Classifier and Naïve Bayes Classifier.The tools used are RASA, machine learning classification algorithms, data extraction etc.