Deep Learning-Based Prediction of Knee Innovative Practices

This project presents a systematic framework employing advanced deep learning techniques for predicting knee osteoarthritis. Leveraging state-of-the-art models in image recognition, joint segmentation, and pathological analysis, our approach aims to streamline the diagnosis process. The integration of Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs) enhances the accuracy and efficiency of predicting knee osteoarthritis. This study represents a significant advancement in medical diagnostics, offering a valuable tool for healthcare professionals to predict and manage knee osteoarthritis, contributing to improved patient care and management.