A HYBRID HUMAN-AI WEB SYSTEM FOR REAL-TIME MENTAL HEALTH COUNSELLING AND CHRONIC DISEASE MANAGEMENT
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Artificial Intelligence, Chronic Disease, E-counselling, Flowise, Web-based
Abstract
This research examines the creation and implementation of an online communication and engagement platform for patients with chronic diseases and their counsellors, designed to enhance mental health support through real-time counselling and intelligent virtual assistance. The paper tackles the shortcomings of current systems, which frequently do not offer true offline functionality but instead require continuous connectivity. Our system is optimized for low-bandwidth environments, integration of AI with human interaction, and accessibility for those with limited digital access. The objective was to develop an interactive, secure, and scalable platform that merges rule-based virtual assistance with live l interaction to provide ongoing, context-sensitive care. The platform was created using Flowise, Firebase, Grop API, and SerpAPI, facilitating secure user enrolment, scheduling of appointments, group support, and immediate communication. Validation in a simulated setting confirmed its effectiveness, showing advancements in data precision, responsiveness, and information dissemination. Security was maintained through HTTPS encryption, encrypted data storage, role-based access controls, and protocols for patient consent and data anonymization. The findings indicated that integrating a Flowise-based assistance with human counsellors enhanced system flexibility, accuracy, and patient engagement. In summary, this study offers a powerful solution for addressing gaps in digital mental health provision, especially for underprivileged communities.
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References
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Copyright (c) 2026 Maaruf Mohammed Lawal, and Abdulrashid Abdulrauf
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