Bone fracture detection and fracture type classification using machine learning

Bone fractures are among the most common orthopedic injuries caused by accidents, falls, and sports-related incidents. Accurate and timely detection of fractures is essential for effective treatment and to prevent further complications. Traditional diagnosis relies on the manual examination of X-ray images by radiologists, which can be time-consuming and may sometimes lead to variations in interpretation. Recent advances in Artificial Intelligence (AI) and Deep Learning have introduced automated techniques that can assist healthcare professionals in analyzing medical images with greater speed and consistency.
This research presents an intelligent bone fracture detection and fracture type classification system using a Convolutional Neural Network (CNN). The proposed model is trained on a publicly available Kaggle bone X-ray dataset containing images of fractured and healthy bones. 
Using Convolutional Neural Network (CNN) we got Accuracy of 95.67%. We can include developing a mobile application for fracture detection using smartphones and tablets.