• Sayema Siddiqua
• Dr P Sripalreddy
• Veeresh

Osteoarthritis, a prevalent joint disorder affecting millions globally, particularly those over 40, often remains undiagnosed or poorly managed in underserved regions like Karnataka, India, due to limited medical resources. KneeCareAI, a web-based platform, addresses this challenge by leveraging deep learning, generative AI, and modern web technologies to enhance osteoarthritis detection and management. The platform offers an interactive, multilingual interface supporting English, Kannada, Urdu, and Hindi, ensuring accessibility for diverse populations. Key features include AI-driven knee X-ray analysis, disease stage prediction, a generative AI chatbot for real-time user queries, and a patient progress monitoring dashboard. Built using HTML, CSS, JavaScript, and Flask, KneeCareAI is device-compatible and incorporates visual elements and gamification to engage elderly patients. This thesis explores the platform’s design, implementation, and evaluation, highlighting its technical innovations and social impact. By providing a scalable, inclusive solution, KneeCareAI aims to transform osteoarthritis care in low-resource settings, contributing to equitable healthcare access and improved patient outcomes.

- Osteoarthritis, KneeCareAI, deep learning, generative AI, web-based platform, healthcare technology, medical imaging, X-ray analysis

"Gen-AI Powered knee-Osteoarthritis Detection Using Deep-Learning and Computer-Vision", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 9, page no.d357-d364, September-2025, Available :http://www.jetir.org/papers/JETIR2509349.pdf

"Gen-AI Powered knee-Osteoarthritis Detection Using Deep-Learning and Computer-Vision", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 9, page no. ppd357-d364, September-2025, Available at : http://www.jetir.org/papers/JETIR2509349.pdf