A Structured and Safety-Aware AI Framework for Digital Health Consultation

DOI

10.2991/978-94-6239-693-7_13How to use a DOI?

Keywords

Digital Health Consultation; Structured Symptom Analysis; Multimodal Health Data; Safety-Aware AI; Avatar-Based Interaction; Preliminary Medical Guidance; Responsible Healthcare AI; Clinical Decision Support

Abstract

The increasing use of digital health consultation systems shows that technology now plays an essential role in identifying health problems and teaching patients. The existing digital health systems depend entirely on text communication which creates problems for users who need assistance and for health information that needs to be shared. Actual systems lack the ability to show users the visual aspects of their symptoms along with their emotional experiences which results in decreased system performance. This research presents an AI-based digital health consultation system which uses real-time avatar interaction together with organized symptom assessment to help users complete their medical consultation. The framework uses clinical reasoning principles to enable users to submit symptoms through text and audio and image methods. Virtual avatars with synchronized lip movements and changing facial expressions help users understand information better while increasing their interaction with the system. The proposed system was evaluated using a disease categorization module that classifies symptoms across five health categories, achieving a mean classification accuracy of 94.9% with low response latency. The framework provides accurate health assessment which uses evidence-based information to create non-diagnostic health assessment results according to experimental test results and confusion matrix evaluation.

Copyright

© 2026 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - S. Arulprasanth
AU  - P. Amudhan
AU  - L. Sherly Puspha Annabel
PY  - 2026
DA  - 2026/06/16
TI  - A Structured and Safety-Aware AI Framework for Digital Health Consultation
BT  - Proceedings of the International Conference on Intelligent Systems for a Sustainable Future (ISSF 2026)
PB  - Atlantis Press
SP  - 112
EP  - 119
SN  - 2589-4919
UR  - https://doi.org/10.2991/978-94-6239-693-7_13
DO  - 10.2991/978-94-6239-693-7_13
ID  - Arulprasanth2026
ER  -