Also regarded as log loss, this function takes the negative log-likelihood of a normalized logit to be equivalent to the desired output and penalizes unlikeliness accordingly.
Published in Chapter:
Healthcare Conversational Chatbot for Medical Diagnosis
Rohan Jagtap (Sardar Patel Institute of Technology, Mumbai, India), Kshitij Phulare (Sardar Patel Institute of Technology, Mumbai, India), Mrunal Kurhade (Sardar Patel Institute of Technology, Mumbai, India), and Kiran Shrikant Gawande (Sardar Patel Institute of Technology, Mumbai, India)
Copyright: © 2021
|Pages: 15
DOI: 10.4018/978-1-7998-3053-5.ch020
Abstract
Medical services are basic needs for human life. There are times when consulting a doctor can be difficult. The proposed idea is an AI-based chatbot that will provide assistance to the users regarding their health-based issues. The state of the art in the aforementioned field includes extractive bots that extract the keywords (i.e., symptoms from the user's input) and suggest its diagnosis. The proposed idea will be a conversational bot, which unlike the QnA bot will take into consideration the context of the user's whole conversation and reply accordingly. Thus, along with symptom extraction, the user will get a better experience conversing with the bot. The user can also normally chat with the chatbot for issues like if the user is not emotionally sound. For example, the bot will console the user if he/she is feeling stressed by recognizing the emotional health of the user.