CNN-based Osteoporosis Risk Assessment and AI-Backed Treatment Advice

CNN-based Osteoporosis Risk Assessment and AI-Backed Treatment Advice

Nidhi Sawant1, Shweta Munde1, Prajakta Mohite1, Mehvish Shaikh1, Nitisha Rajgure2

1BE Students, Department of Computer Engineering, Zeal College of Engineering and Research, Pune, Maharashtra, India

2Professor, Department of Computer Engineering, Zeal College of Engineering and Research, Pune, Maharashtra, India

Abstract:

Osteoporosis, a progressive bone disease, significantly increases fracture risk. Early detection is vital for preventative measures. This study investigates the application of Convolutional Neural Networks (CNNs) for automated osteoporosis detection using medical images. We propose a CNN model trained on a labelled dataset of knee x-ray images to classify normal and osteoporotic bone structures. The paper talks about the model development, training process, and evaluation for accuracy in osteoporosis detection. The patients using the proposed model will be connected with resources for diagnosis, treatment, and support.

Keywords: Osteoporosis, Bones, Fractures, Assessment, Detection, Prediction, Treatment, Convolutional Neural Networks (CNN), X-Ray, Bone Mineral Density (BMD), Dual-Energy X-Ray Absorption (DXA), Machine learning, Medical Image Data, Image labelling.