Mammography Based Classification of Benign and Malignant Masses Using Artificial Neural Network
| Author(s) | : | Sanskriti Kathale, Prof. Sampada Massey |
| Institution | : | Shri Shankaracharya Group of Institutions, Dept. of Computer Science and Engineering, Bhilai, Chhattisgarh, India |
| Published In | : | Vol. 4, Issue 9 — September 2017 |
| Page No. | : | 396-404 |
| Domain | : | Engineering |
| Type | : | Research Paper |
| ISSN (Online) | : | 2348-4470 |
| ISSN (Print) | : | 2348-6406 |
Artificial neural network has been broadly utilized as a part of different fields as a wise instrument as oflate, for example, artificial knowledge, design acknowledgment, medicinal determination, machine learning et cetera.The characterization of breast disease is a therapeutic application that represents an awesome test for analysts andresearchers. As of late, the neural network has turned into a well-known device in the order of malignancy datasets.Significant detriments of artificial neural network (ANN) classifier are because of its slow merging and continually beingcaught at the neighborhood minima. In this paper we proposed a Nobel method for finding the breast cancer in thepatent. We have used artificial neural network to classify the disease. Our proposed mechanism effectively classify thecancerous and non-cancerous mammogram of the female breast.
Sanskriti Kathale, Prof. Sampada Massey, “Mammography Based Classification of Benign and Malignant Masses Using Artificial Neural Network”, International Journal of Advance Engineering and Research Development (IJAERD), Vol. 4, Issue 9, pp. 396-404, September 2017.
