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Published Paper Details:
MACHINE LEARNING MODELS FOR EARLY DETECTION OF BREAST CANCER
Authors
Uzma Nazir,Mandeep Kaur
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Keywords
Breast Cancer Detection, Machine Learning, Random Forest, Logistic Regression, Decision Tree, Support Vector Machine.
Abstract
This research is justified from the scientific field since through the development of an intelligent system will support mammographic analysis in timely detection of breast tumors thus generating an innovative idea that contributes to the science of health. From the financial field it is justified that this system is not very expensive compared to other systems that are in the technological market, it will also reduce the waiting time for a timely and early diagnosis of breast cancer, thus obtaining more patients attended that will bring high prestige to the institution. Continuing with the social sphere, it is justified since it intends to support the mammographic analysis, where there will be a minimum margin of error and in addition to helping the oncology area by having a timely diagnosis. Also this system indirectly benefit the students of the medical career, as well as the specialists in charge of this area. Finally, this present investigation is justified technologically since present technologies will be used as much as software and hardware that will allow this intelligent system to be carried out in order to support the radiologist with the mammographic analysis. However, this research on breast cancer, which successfully carried out the calculation analysis, using various models of Machine Learning like logistic regression, support vector machine, decision tree, and random forest Consequently, Logistic Regression with dependent and independent variables results in the test data accuracy value of 96%. Thereafter, SVM vide linear hyperplane determining the affected patients with breast cancer and number of predictions achieved 97% of accuracy. Subsequently, the Decision Tree modeling with Random Forest achieved 96% of accuracy collectively.
IJCRT's Publication Details
Unique Identification Number - IJCRT2308414
Paper ID - 242915
Author type - Indian Author
Page Number(s) - d853-d870
Pubished in - Volume 11 | Issue 8 | August 2023
DOI (Digital Object Identifier) -
No Of Downloads - 104
Author Country - India, 121003, Faridabad, Faridabad, 121003, Science and Technology
Publisher Name - IJPUBLICATION | www.ijcrt.org | ISSN : 2320-2882
E-ISSN Number - 2320-2882
Published Paper PDF : - http://www.ijcrt.org/papers/IJCRT2308414
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Uzma Nazir,Mandeep Kaur, "MACHINE LEARNING MODELS FOR EARLY DETECTION OF BREAST CANCER", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.11, Issue 8, pp.d853-d870, August 2023, Available at :http://www.ijcrt.org/papers/IJCRT2308414.pdf
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ISSN: 2320-2882 Impact Factor: 7.97 and ISSN APPROVED Journal Starting Year (ESTD) : 2013
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ISSN: 2320-2882 Impact Factor: 7.97 and ISSN APPROVED Journal Starting Year (ESTD) : 2013
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