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@article{176532,
        author = {Prof. Ayesha Asif Sayyad and Dr. Rajesh Keshavrao Deshmukh},
        title = {INTELLIGENT MEDICAL DIAGNOSTIC SYSTEM FOR OSTEOARTHRITIS: A DEEP LEARNING APPROACH AND COMPARISON},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {11},
        pages = {5811-5823},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=176532},
        abstract = {Osteoarthritis (OA) is a disabling joint disease, predominantly affecting the elderly and the obese, and resulting in compromised quality of life and heightened frailty. This review article addresses the existing diagnostic techniques employed in OA that largely depend upon clinical examination and imaging techniques. These techniques might be deficient in efficiency and accuracy, therefore, such complicated diagnostic systems are required. This article suggests an Intelligent Medical Diagnostic System for Osteoarthritis based on deep learning and medical imaging. Combing medical images and deep features, the system will identify and classify OA, especially of the knee joint, appropriately. The problems regarding irrelevant feature selection and database management issues of large databases are solved, as well as research on Magnetic Resonance Imaging (MRI) methods for detection and OA classification. The review offers detailed discussion on location strategy, feature extraction methods, and classification models suitable for OA diagnosis, and provides recent development and future direction.},
        keywords = {OA, Classification Methods, Deep Learning, Feature extraction, Medical Imaging, MRI.},
        month = {April},
        }