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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM63796
Volume:
10 |
5 |
May 2026
Pages:
1-7
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
Department of Computer Science and Engineering
Acropolis Institute of Technology and Research
Department of Computer Science and Engineering
Acropolis Institute of Technology and Research
Department of Computer Science and Engineering
Acropolis Institute of Technology and Research
Department of Computer Science and Engineering
Acropolis Institute of Technology and Research
Department of Computer Science and Engineering
Acropolis Institute of Technology and Research
Department of Computer Science and Engineering
Acropolis Institute of Technology and Research
Proactive health management is still hampered by limited access to preventative healthcare services and the fragmentation of digital medical technologies. This article presents Cura Sphere, an intelligent AI-driven platform designed to offer accessible and integrated health support via a single digital environment. The system provides symptom assessment, risk assessment for chronic diseases, and tailored wellness advice through a single interface by fusing machine learning-based prediction models with conversational generative AI. The platform, which is based on a modular Django design, offers task-oriented lifestyle tracking, automatic report production, structured health data management, secure user identification, and mental wellness support. The suggested solution takes a comprehensive approach that combines behavioral monitoring, conversational interaction, and predictive analytics, in contrast to stand-alone symptom-checking apps. Improved usability and sustained engagement while preserving data are indicated by experimental evaluation. The main innovation of the system is its holistic approach to wellbeing, which combines personalized lifestyle recommendations, mental health monitoring, predictive health modeling, and symptom analysis into a single conversational interface. This all-encompassing approach encourages accessible preventative treatment across a range of demographic groups while empowering users toward proactive healthcare management and removing reliance on different applications.
KEYWORDS
The proposed AI-powered productivity and health assistant offers a thorough and integrated method of managing digital healthcare. The solution bridges the gap between preventative healthcare and everyday lifestyle assistance by integrating machine learning-based disease prediction, conversational AI-driven health advising, mental well-being monitoring, and intelligent task management. While the contact and feedback mechanism encourages ongoing improvement through user participation, the automated health report production with email delivery guarantees accessibility and long-term health tracking. The community support feature also encourages peer support and collaborative learning, which improves the user experience in general. The system is a proactive first step toward health awareness and self-management, but it is not meant to take the place of expert medical consultation. The platform helps users make better decisions and enhance their general well-being by providing them with individualized guidance, predictive insights, and helpful digital tools.
[1] Ada Health, “AI-powered symptom checker,” [Online]. Available: https://ada.com [2] WebMD, “Symptom Checker,” [Online]. Available: https://symptoms.webmd.com/ [3] HealthifyMe, “AI-powered fitness and nutrition app,” [Online]. Available: https://healthifyme.com [4] Mayo Clinic, “Symptom Checker,” [Online]. Available: https://www.mayoclinic.org/symptom-checker [5] World Health Organization (WHO), “Global strategy on digital health 2020–2025,” 2021. [Online]. Available: https://www.who.int/publications/i/item/9789240020924 [6] A. B. Sawad, J. S. Rashid, and M. A. Hossain, “A systematic review on healthcare artificial intelligent conversational agents for chronic conditions,” Sensors, vol. 22, no. 7, 2022. [7] T. Schachner, A. Keller, and T. Wangenheim, “Artificial intelligence-based conversational agents for chronic conditions: Systematic literature review,” Journal of Medical Internet Research, vol. 22, no. 9, 2020. [8] M. H. Kurniawan et al., “A systematic review of AI-powered chatbot interventions for managing chronic illness,” Annals of Medicine, vol. 56, no. 1, 2024. [9] D. Bhatt, S. Ayyagari, and A. Mishra, “A scalable approach to benchmarking the in-conversation differential diagnostic accuracy of a health AI,” arXiv preprint arXiv:2412.12538, 2024. [10] B. Wen et al., “Leveraging large language models for patient engagement: The power of conversational AI in digital health,” arXiv preprint arXiv:2406.13659, 2024.
Publication Date
5/22/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
Funding Information
No funding information available for this research.
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