• Bhavana B
• Priyanka M

This paper presents a novel technology-driven platform designed to support individuals with dyslexia, particularly in underserved regions where access to diagnostic and educational resources is limited. Dyslexia, affecting 10-20% of the global population, often goes undiagnosed in rural and semi-urban areas due to a lack of specialists, affordable tools, and culturally relevant solutions. The proposed system leverages Machine Learning, generative AI, and modern web technologies (HTML, CSS, JavaScript, and Flask) to create a scalable, multilingual, and user-friendly platform. Key features include a symptom checker, predictive analytics, a real-time chatbot for personalized assistance, and a dashboard for tracking progress, all tailored to support languages like English, Kannada, Urdu, and Hindi. The platform incorporates gamification and visual aids to enhance engagement, especially for younger users, and fosters community interaction for shared support. This study explores the system’s architecture, implementation, and evaluation, emphasizing its potential to improve dyslexia identification and management. By addressing technical, cultural, and social challenges, this work contributes to inclusive education and healthcare, offering a scalable model for supporting individuals with learning disabilities in resource-constrained settings.

DyslexiaAI, Machine learning, generative AI, web-based platform, healthcare technology, medical imaging

"Gen-AI Powered Dyslexia-Prediction Using Machine-Learning ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 9, page no.d643-d650, September-2025, Available :http://www.jetir.org/papers/JETIR2509384.pdf

"Gen-AI Powered Dyslexia-Prediction Using Machine-Learning ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 9, page no. ppd643-d650, September-2025, Available at : http://www.jetir.org/papers/JETIR2509384.pdf