INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2456-4184 | Impact factor: 8.76 | ESTD Year: 2016
Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.76 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)
Breast cancer poses a severe exposure to women because it is one of the most prevalent diseases in women. Healthy cells in the breast begin to alter and expand out of control to form a tumor, which is a mass or sheet of cells. A tumor may be benign or malignant. Malignant describes a cancerous tumor's capacity to grow and spread to various body parts. A benign tumor is one that is still growing and has not yet spread. Given the constantly increasing danger of death from breast cancer, early cancer detection has become absolutely essential. Based on deep learning, it may be possible to predict breast cancer. Deep learning algorithm neural network is constructed for detection of breast cancer using different datasets namely Wisconsin Breast Cancer Dataset (WBCD), MIAS Mammography Dataset and Breast Cancer Histopathological Database (Breakhis). We have collected dataset and applied pre-processing algorithm for the data and then we splitted dataset in training and testing purpose and then we implemented model on training dataset. Three regular Machine Learning models, namely logistic regression (LR), decision tree (DT), random forest (RF) were compared with the Deep Learning Neural Network (NN). The accuracy of cancer detection by experienced physicians is 78%, while deep learning techniques can provide accuracy of up to 98%.
Keywords:
Breast Cancer, Malignant, Benign, Deep learning, NN, Machine learning, Decision Tree, Random Forest, Logistic Regression.
Cite Article:
"Breast Cancer Prediction using Deep Learning", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.8, Issue 4, page no.f284-f292, April-2023, Available :http://www.ijnrd.org/papers/IJNRD2304530.pdf
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ISSN:
2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
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