Bone Fracture Identification using ANN Algorithm and Comparing the Accuracy with SVM Algorithm

Major aim of this research is to detect the bone fracture using Novel Artificial Neural Network (Novel ANN) and compare the outcomes with Support Vector Machine (SVM). In this work X-ray picture is used to diagnose fractures in the bones. Total 40 samples were used for this analysis as Two groups with machine learning algorithms Novel ANN and SVM. Group 1 with 20 samples using Novel ANN and Group 2 with 20 samples using SVM. Samples obtained with pretest power 80%. The examinations have been performed to check the accuracy performance of the Novel ANN and SVM model using the MATLAB software tool. The accuracy of the proposed Novel ANN model is achieved as 93.09% of the solid bone and SVM model achieves 86.14% accuracy, obtained significance value (p=0.000). For the given image dataset, the proposed Novel ANN model achieves significantly better accuracy than the SVM method.