Analysis and Classification of Bone Fractures Using Machine Learning Techniques

Human bones are the hard organs that protect vital such as heart, lungs, and other internal organs. Fractures of a prevalent issue among humans. Bone fractures may develop from an accident or another circumstance when there is great pressure on bones. It be difficult time-consuming to determine site fracture in patient who suffering discomfort. The manual examination during radiological interpretation error-prone process. This result erroneous detection, poor healing, extensive procedure. So, this research proposed effective approach rectifying bone with inclusion latest technologies. solution by employing Deep learning model. Moreover, novel concept classification also incorporated. Firstly; MURA dataset was collected Stanford. Secondly; model used techniques like DCNN (Deep Convolution Neural Network) use Alex Net Bones classified into fractured non-fractured through approach. created using Google Colab. trained repeating several experiments. performance evaluated based accuracy. suggested results were compared baseline algorithms well. Consequently, findings work will useful for medical industry.