Knee Osteoarthritis Detection Using X-Ray Images from an Explainable AI (XAI) Perspective

XAI methods include:

• Grad-Cam
• Integrated Gradients
• Lime

CNN Model : VGG16 + ResNet50

This project represents a pioneering effort in bridging the gap between cutting-edge AI technologies and the healthcare sector's pressing need for transparency and interpretability. Leveraging a combined CNN model architecture incorporating renowned models like VGG16 and ResNet50, alongside Explainable AI Libraries such as Grad-Cam, Lime, and Integrated Gradients, our initiative seeks to enhance the interpretability and transparency of AI-driven healthcare solutions. By enabling healthcare professionals, particularly doctors, to understand and trust the decisions made by AI systems, we aim to foster a collaborative environment where human expertise synergizes with artificial intelligence to deliver optimal patient care. This endeavor stands as a testament to our commitment to advancing healthcare through innovative and ethically responsible AI applications.