Osteoporosis Risk Prediction Using Enhanced Support Vector Machine over Artificial Neural Network

Aim: The aim of this study is to predict the osteoporosis risk by using the proposed Support Vector Machine(SVM) Algorithm over Artificial Neural Network(ANN) Algorithm. Materials and Methods: Sample groups that are considered in this project is CT Scan dataset that can be classified into two, one for training data and other for testing data, Dataset are tested using 233.9s for G-power to determine the sample size and for train set analysis.Nearly 215 CT Scan images have been used in each group for testing of cancer. Results: The Enhanced Support Vector Machine algorithm has better efficiency with 83% accuracy when compared to Artificial Neural Network algorithm's 71%. Statistical significance difference (two-sided) is 0.01 (p<0.01). Conclusion: Support Vector machine algorithm performed significantly better than the Artificial Neural network algorithm.