Issue |
ITM Web Conf.
Volume 44, 2022
International Conference on Automation, Computing and Communication 2022 (ICACC-2022)
|
|
---|---|---|
Article Number | 03020 | |
Number of page(s) | 5 | |
Section | Computing | |
DOI | https://doi.org/10.1051/itmconf/20224403020 | |
Published online | 05 May 2022 |
Intelligent Medical Chatbot System For Women’s Healthcare
1 Department of Information Technology, RAIT, D. Y. Patil Deemed to be University Nerul
2 Department of Information Technology, RAIT, D. Y. Patil Deemed to be University Nerul
3 Department of Information Technology, RAIT, D. Y. Patil Deemed to be University Nerul
4 Department of Information Technology, RAIT, D. Y. Patil Deemed to be University Nerul
Email: shrushtipolekar@gmail.com
Email: shivaniwakde1211@gmail.com
Email: mayuresh.pandare21@gmail.com
Email: priyanka.shingane@rait.ac.in
Even today talking about women health is big taboo in India. The society is unbiased about women especially about their health issues hence they face disparity in the society. Women feel hesitant to talk about or speak about their health issues or problems openly. Thus, the goal of this chatbot is to help women to find information and remedial solutions about their health. Query is processed by the bot and response will be displayed on web application. This chatbot will provide helpful information instantly. It will also provide prediction about the disease that the women might be suffering.So this bot will help to make Right decision and give right advice to women on 24/7 basis. It will act as an helping hand for working women to keep check on their health in their busy routine. At the same time this will also help women in rural areas who are apprehensive to talk about their health issues publicly.
© The Authors, published by EDP Sciences, 2022
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.