E-Health Bot to Change the Face of Medicare

EasyChair Preprint 4856

Abstract

Chatbot or conversational bot is a tool to ease the communication between human beings and computers. When someone talks to a chatbot, it seems as if you are talking to an actual human being. Chatbots carry out conversation in auditory and textual manner. Chatbots work on the principles of Artificial Intelligence and are automated devices. Their response is based upon the input of the user. They analyze the request, identify intent and entities and then compose their reply which may be data from the database or an API (application programming interface) call. These devices are trained with the help of actual data. The device matches the questions asked by the user to the best suitable answer using tools and models of machine learning. Chatbots seem to be self-sufficient after they go live but human intervention is very crucial in its configuration, training and implementation. Since the database for outputs is limited, it is possible that chatbot encounters an unknown query which is to be solved by a human being. However, chatbots do hold an advantage over human beings as they are available 24/7 and have access to huge amount of information. These chatbots use API for providing response to different requests of the user. This paper proposes the idea of a new chatbot which will assist the users with their medical needs, the Medicbot. This chatbot will be able to perform multiple functions with the combination of various Artificial Intelligence forms such as semantic understanding and natural language processing. Medicbot will be operated with the help of a virtual assistance (serves the purpose of a personal assistant) known as Medico.

Keyphrases: Artificial Intelligence, Chatbot, Natural Language Processing, e health bot, machine learning, natural language understanding

@booklet{EasyChair:4856,
  author    = {Tushar Tanmay and Akanksha Bhardwaj and Shilpi Sharma},
  title     = {E-Health Bot to Change the Face of Medicare},
  howpublished = {EasyChair Preprint 4856},
  year      = {EasyChair, 2021}}