CAD Tool for Prediction of Knee Osteoarthritis (KOA)

Knee Osteoarthritis (KOA) stands as a prevalent chronic joint condition, impacting individuals globally, especially the elderly. The imperative for timely detection and intervention in curbing OA progression and mitigating associated discomfort cannot be overstated. This paper introduces innovative predictive analytics tool, amalgamating state of the art machine learning and medical imaging methods in anticipating onset and progression of Knee OA. A Flask-based website hosts the model, integrating the MobileNetV2 neural network renowned for its superior accuracy. Radiographic data and clinical parameters undergo meticulous analysis, offering healthcare providers preemptive insights for early interventions and personalized treatment strategies. The system aspires to revolutionize Knee OA management, heralding an era of proactive healthcare that enhances individual well-being and mobility. The discussion on the importance of predicting Knee OA underscores the critical role of early intervention, resource optimization, and advancements in treatment modalities. This predictive assessment holds transformative potential for healthcare, fostering not only healthier but also more resilient communities. The paper meticulously details the methodology employed, the resultant findings, and their broader implications, making a significant contribution to the ongoing discourse on proactive healthcare solutions for musculoskeletal conditions.