TinyML-Based Lightweight AI Healthcare Mobile Chatbot Deployment
Each patient was assigned a unique ID, and their data were securely stored for further consultation and diagnosis via hospital management. This research demonstrates faster patient data recording and increased security compared to existing AI-based healthcare solutions, as all processes occur within the local host.
Authors
- M. Poonkodi
- Anita Christaline Johnvictor (ORCID: https://orcid.org/0000-0001-5884-5733)
- A. Sankar
- Thinesh VS
Institutions
- Tejas Networks (India) (IN)
- Vellore Institute of Technology University (IN)
Publication Details
- Journal
- Journal of Multidisciplinary Healthcare
- Published
- 2024-11-01
- DOI
- https://doi.org/10.2147/jmdh.s483247
- Citations
- 11
- Primary Topic
- Artificial Intelligence in Healthcare
- Type
- article
- Field-Weighted Citation Impact
- 7.79
Funders
- Vellore Institute of Technology, Chennai
- VIT University