| Autor: |
S. Nirmala Sugirtha Rajini, J. Jacinth Salome, S. Leena Nesamani, M. S. Josphine |
| Rok vydání: |
2021 |
| Předmět: |
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| Zdroj: |
Advances in Automation, Signal Processing, Instrumentation, and Control ISBN: 9789811582202 |
| DOI: |
10.1007/978-981-15-8221-9_35 |
| Popis: |
Breast cancer is one of the most threatening diseases among women worldwide because of its painful treatment process which provides a temporary cure but becomes fatal in most cases. It is a complex health problem which possesses a high mortality rate. But the good news is that it is completely curable if diagnosed during the early stage. Breast cancer is caused due to the uncontrolled multiplication of abnormal breast cells that forms a tumor in the breast area. The tumor could be either benign (non-cancerous) or malignant (cancerous) one. The malignant cells may spread from the original tumor area to neighboring lymph nodes or to other distant parts of the body, in which case it is called metastasis. The symptoms of breast cancer may include pain in the breast, swelling of the breast, thickening of the breast tissues, dimpling of the breast or as a lump in the breast or the armpit. Many types of research have been made to predict breast cancer accurately. This paper reviews and compares three different models using the SVM (Support Vector Machine) method that is tried and tested to detect the presence of breast cancer with greater accuracy. Later in this study, a novel system that employs Artificial Neural Network and Multi-Level Support Vector Machine model is employed for the detection of breast cancer. The proposed system employs the mini-MIAS database. The accuracy of the intelligent system has proved to be better than the other approaches that have been studied. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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