Authors

Sivaguru S

Department of Electronics and Communication Engineering, AVS College of Engineering, Salem, Tamilnadu, India

Sathish Kumar M

Department of Electronics and Communication Engineering, AVS College of Engineering, Salem, Tamilnadu, India

Karthik D

Department of Electronics and Communication Engineering, AVS College of Engineering, Salem, Tamilnadu, India

Abstract

The integration of Artificial Intelligence (AI) and Large Language Models (LLMs) has revolutionized modern healthcare by enabling intelligent, interactive, and personalized digital health services. The growing demand for timely medical guidance, increasing prevalence of chronic diseases, and limited availability of healthcare professionals have accelerated the adoption of AI-driven virtual healthcare systems. This study presents the design and development of an AI-powered personalized healthcare assistant based on Large Language Models to provide real-time health support through natural language conversations. The proposed framework enables users to interact with the system for symptom assessment, health-related inquiries, medication guidance, preventive healthcare recommendations, nutritional advice, and general wellness support. By utilizing the contextual understanding capabilities of advanced LLMs, the assistant interprets user queries, retrieves relevant medical knowledge, and generates coherent, context-aware, and user-friendly responses. To further enhance personalized healthcare, the system incorporates an image-based food recognition module that identifies food items from uploaded images and provides nutritional analysis, calorie estimation, and dietary recommendations to encourage healthier eating habits. The overall architecture consists of secure user authentication, conversational AI, medical knowledge integration, personalized recommendation engines, and adaptive learning mechanisms that continuously improve system performance based on user interactions and feedback. Special emphasis is placed on data privacy, secure information handling, and ethical AI practices to ensure the confidentiality and reliability of healthcare services. Experimental evaluation indicates that the proposed healthcare assistant provides accurate, responsive, and personalized medical support, improves user engagement, and facilitates convenient access to essential health information while complementing, rather than replacing, professional medical consultation. The proposed framework demonstrates significant potential for preliminary health assessment, patient education, preventive care, nutritional counseling, and digital healthcare management, thereby contributing to the advancement of intelligent, accessible, and patient-centric healthcare solutions.

Keywords

Artificial Intelligence (AI) Large Language Models (LLMs) Personalized Healthcare Conversational AI Virtual Health Assistant Natural Language Processing (NLP) Clinical Decision Support Digital Healthcare.

Citation of this Article

Sivaguru S, Sathish Kumar M, & Karthik D. (2026). Leveraging Large Language Models for Intelligent Personalized Healthcare Support. Current Journal of Engineering and Science Research. 3(8), 1-11. Article DOI: https://doi.org/10.47001/CJESR/2026.308001

Licence Copyright (c) 2026 Current Journal of Engineering and Science Research. This work is licensed under a Creative Commons Attribution Non Commercial 4.0 International Licence.

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