Detection of Osteoporosis and Osteoarthritis Using Deep Learning Algorithms

Osteoporosis and Osteoarthritis in the knee are disorders that commonly affect the musculoskeletal system of an individual. It is majorly prevalent in elderly people and has an impact on the quality of their lives. The late diagnosis of these diseases leads to joint dysfunction, decreased mobility, and dependency on regular activities. Therefore, in the present article of review, we discussed works that applied deep learning methods, such as convolution neural networks (CNN), support vector machines and many more such algorithms for feature extraction and classification for early, precise, and rapid disease prediction. It involves the process of acquiring scan images, preprocessing and application of deep learning algorithms to identify the presence or absence of the diseases. Finally, in order to determine the efficiencies, the model's performance is compared and the best model is recommended for real time applications.