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- W4312659304 abstract "Cancer of the breast is a common cause of death in women. It is the second most origin of cancer deaths in women. For classifying breast tumors using image processing techniques, the researchers had developed image classification systems. Breast cancer disease becomes complicated as the causes remain unspecified. The regular indication of this disease masses and micro calcifications which is appeared on mammograms. They can be used to improve initial diagnosis approaches over time, which is important for women’s lives. Mammography is an x-ray of the breasts to execute in the absence of symptoms. X-ray mammography is the major test used for screening and processing is the key to developing breast cancer. The first method comprises determining the cells present with various processes. An abnormal cell growth that serves no purpose is a tumor. In this work machine learning technique-SVM is used to detect the breast cancer and this work also predict the various stages of breast cancer. Proposed model results in 97% accuracy which is better than previous work." @default.
- W4312659304 created "2023-01-05" @default.
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- W4312659304 date "2022-10-16" @default.
- W4312659304 modified "2023-09-27" @default.
- W4312659304 title "Sustainable Health Care System for Cognitive Breast Cancer Detection using Machine Learning" @default.
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- W4312659304 doi "https://doi.org/10.1109/mysurucon55714.2022.9972395" @default.
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