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

被引：0

作者：

Jagadeesh, A. ^{[1
]}

Kumar, Senthil S. ^{[1
]}

机构：

[1] Saveetha Univ, Saveetha Inst Med & Tech Sci, Saveetha Sch Engn, Dept Comp Sci & Engn, Chennai 602105, Tamil Nadu, India

来源：

JOURNAL OF PHARMACEUTICAL NEGATIVE RESULTS | 2022年 / 13卷

关键词：

Osteoporosis risk prediction; Enhanced Support Vector Machine; Artificial Neural Network; Bone Cancer; CT Scan;

D O I：

10.47750/pnr.2022.13.S04.191

中图分类号：

R9 [药学];

学科分类号：

1007 ;

摘要：

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.

引用

页码：1602 / 1611

页数：10

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