A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2018; you can also visit the original URL.
The file type is application/pdf
.
Using Five Machine Learning for Breast Cancer Biopsy Predictions Based on Mammographic Diagnosis
2017
International Journal of Engineering Technologies IJET
Breast cancer is one of the causes of female death in the world. Mammography is commonly used for distinguishing malignant tumors from benign ones. In this research, a mammographic diagnostic method is presented for breast cancer biopsy outcome predictions using five machine learning which includes: Logistic Regression (LR), Linear Discriminant Analysis (LDA), Quadratic Discriminant Analysis (QDA), Random Forest (RF) and Support Vector Machine (SVM) classification. The testing results showed
doi:10.19072/ijet.280563
fatcat:dmlzoogvtff73mwuv2o5ce32me