Enhanced Health Care System with Chatbot and Voicebot Using Deep Learning
Providing adequate healthcare, for seniors and those with reading difficulties or language barriers poses challenges in areas today where people face obstacles in accessing reliable medical advice. Our solution involves the creation of an AI powered Medical Chatbot aimed at making healthcare assistance easier to access and enhancing communication, between individuals and technology. The chatbot allows users to share their symptoms using text or voice inputs and provides tailored advice, along with suggestions for precautions and dietary changes. With its voice interaction capability driven by state-of-the-art speech recognition technology the chatbot is particularly convenient for those who find typing or reading challenging. Moreover, it offers support, for languages, including dialects to ensure that healthcare information reaches a wide range of people. The tool uses Natural Language Processing (or NLP for short) along, with Deep Learning (DL) to deliver contextually relevant answers. One standout aspect is its ability to learn on its own. This enables the chatbot to consistently enhance its database with the details on diseases, therapies and developments, in the field. Utilizing AI technologies, along with a user centered approach to design is the goal of this chatbot. To make healthcare more accessible for everyone by providing reliable medical assistance that is inclusive to all users' needs and backgrounds. This innovative approach marks an advancement, in improving public health results and overcoming the obstacles that have hindered quality healthcare services for so long.
Authors
- Karakavalasa Sreedhar
- A. Mahesh Babu (ORCID: https://orcid.org/0000-0002-5475-1825)
- Pradeep Kumar Mahapatro
- Savirigana Inusha
- Konkena Niteeshkumar
- Reshi Pulla
Institutions
- Aditya Birla (India) (IN)
Publication Details
- Published
- 2025-06-05
- DOI
- https://doi.org/10.1109/wams64402.2025.11158930
- Primary Topic
- Artificial Intelligence in Healthcare
- Type
- article
- Field-Weighted Citation Impact
- 0.00