(untitled) (Journal of Pharmaceutical Negative Results, 2022)
Aim: The aim of this study is to detect bone cancer by using the proposed Novel Convolutional Neural Network over SupportVector Machine Algorithm. Materials and Methods: Sample groups that are considered in this project is CT Scan dataset that can be classified into two, one for Convolutional Neural Network and other for Support Vector Machine, 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 ofcancer. Results: Support Vector Machine algorithm has better efficiency (87%) when compared to Convolutional neural Networkalgorithm efficiency (78%). Statistical significance difference (two-sided) is 0.01 (p<0.01). Conclusion: Support Vector Machine algorithm performed significantly better than the Convolutional Neural Network algorithm.