Authors - Jyoti Patil Devaji, Sushma Garawad, Nirmala S. R., Suneeta V. B. Abstract - This study proposes the use of deep neural networks (DNNs) for the classification and diagnosis of knee osteoarthritis (KOA), a common chronic joint ailment characterized by a wide range of symptoms. A number of health-related criteria, including age, gender, body mass, hormone profile, and genetic predisposition, must be evaluated in order to make an accurate diagnosis of KOA. Using deep learning algorithms to accurately classify the severity of KOA is the main goal of this research. The suggested method classifies separate subgroups according to factors such as age, sex, and degree of obesity by using self-reported clinical characteristics. The superiority of deep learning for KOA diagnosis has also been demonstrated by a comparison analysis that was done to assess the performance of the suggested DNN versus conventional machine learning models.
