AI-Based Personal Health & Lifestyle Assistant
Authors
Department of Information Technology Vasantdada Patil Pratishthan’s College of Engineering & Visual Arts, Sion, Mumbai (India)
Department of Information Technology Vasantdada Patil Pratishthan’s College of Engineering & Visual Arts, Sion, Mumbai (India)
Department of Information Technology Vasantdada Patil Pratishthan’s College of Engineering & Visual Arts, Sion, Mumbai (India)
Department of Information Technology Vasantdada Patil Pratishthan’s College of Engineering & Visual Arts, Sion, Mumbai (India)
Department of Information Technology Vasantdada Patil Pratishthan’s College of Engineering & Visual Arts, Sion, Mumbai (India)
Article Information
Publication Timeline
Submitted: 2026-03-26
Accepted: 2026-03-31
Published: 2026-04-10
Abstract
This paper presents the design and development of an AI-Based Personal Health & Lifestyle Assistant system that helps users manage their health in a smarter and easier way. The system combines different features such as disease prediction, chatbot support, hospital search, and diet planning into one platform.
The disease prediction module uses machine learning to analyze user symptoms and suggest possible health conditions. A chatbot is included to answer health-related questions and guide users. The hospital locator helps users find nearby medical facilities using location services, and the diet planner provides personalized meal suggestions based on user needs.
The system is built as a web-based application for easy access and smooth user interaction. Testing results show good accuracy in disease prediction and effective chatbot responses, along with positive user feedback.
Overall, the system helps users take better care of their health by providing early guidance, useful suggestions, and easy access to healthcare information.
Keywords
Artificial Intelligence, Machine Learning, Disease Prediction, Chatbot, Diet Planning, Healthcare System
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References
1. A. Kumar and P. Singh, “AI-Based Symptom Checkers in Primary Healthcare,” Journal of Medical Internet Research, vol. 26, no. 3, pp. 142–151, 2024. [Google Scholar] [Crossref]
2. X. Chen and M. Rodriguez, “Natural Language Processing for Healthcare Chatbots,” Artificial Intelligence in Medicine, vol. 150, pp. 102–119, 2024. [Google Scholar] [Crossref]
3. R. Sharma and L. Thompson, “Machine Learning in Personalized Nutrition Planning,” Journal of Nutritional Science, vol. 18, pp. 77–92, 2024. [Google Scholar] [Crossref]
4. E. Wilson and S. Garcia, “Integrated Digital Health Platforms: Architecture and Implementation,” Healthcare Technology Review, vol. 12, no. 4, pp. 201–215, 2024. [Google Scholar] [Crossref]
5. J. Park and D. Williams, “User Acceptance of AI-Based Healthcare Assistants,” International Journal of Human–Computer Studies, vol. 176, pp. 35–49, 2024. [Google Scholar] [Crossref]
6. N. Gupta, V. Patel, and S. Ray, “Wearable IoT and AI for Continuous Patient Monitoring,” IEEE Access, vol. 13, pp. 19402–19415, 2025. [Google Scholar] [Crossref]
7. L. Zhao and F. Torres, “HealthGPT: Transformer-Based Conversational Models for Personalized Medicine,” ACM Computing Surveys, vol. 57, no. 2, pp. 1–24, 2025. [Google Scholar] [Crossref]
8. D. Patel, S. Ray, and R. Mehta, “Ethical Considerations in AI-Driven Healthcare,” International Journal of Digital Ethics, vol. 9, no. 1, pp. 44–58, 2023. [Google Scholar] [Crossref]
9. M. Lee, J. Kim, and Y. Chen, “Federated Learning for Privacy-Preserving Medical Data Analysis,” IEEE Transactions on Neural Networks and Learning Systems, vol. 36, no. 5, pp. 2231–2245, 2024. [Google Scholar] [Crossref]
10. P. Verma and A. Banerjee, “Cloud-Based AI Framework for Preventive Health Monitoring,” IEEE Journal of Biomedical and Health Informatics, vol. 28, no. 1, pp. 115–128, 2025. [Google Scholar] [Crossref]
11. R. Ahmed, K. Yadav, and M. Chen, “Explainable AI in Healthcare: Bridging Transparency and Trust,” Frontiers in Artificial Intelligence, vol. 7, pp. 84–97, 2024. [Google Scholar] [Crossref]
12. S. Deshmukh and T. Roy, “A Comparative Analysis of AI-Powered Chatbots for Clinical Applications,” IEEE Internet of Things Journal, vol. 11, no. 6, pp. 4329–4342, 2025. [Google Scholar] [Crossref]
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