Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/305680
Title: An Improved Feature Extraction Method for Early Prediction of Breast Cancer Using Machine Learning Algorithm
Researcher: Arivazhagan N
Guide(s): Kottilingam.K
Keywords: Computer Science
Computer Science Information Systems
Engineering and Technology
University: SRM University
Completed Date: 2020
Abstract: Cancer is an extra cell growth in the body due to some genetic and other reasons if it is not identified early, it causes death. There are different types of cancers in the body, some cancers are more dangerous if we find it in earlier stages, it is treatable. Usually, the stages can be classified as a stage of diagnostics, initial stage, second stage, third stage, and the fourth stage. newlineAmong all cancer types, women Breast cancer is a major health issue that is yet to be solved. In the US, by 2020, around 1,735,350 new malignant cancer cases are expected to emerge which might lead to a death toll of 609,640. The key solution to reduce the mortality rate in the early detection of malignant cancer. To achieve effective early detection, clinical practices, and diagnostic techniques should be equipped with enhanced cancer image processing methods. Mammogram images are used to identify the breast cancer cells which is only used in this research. The modern lifestyle changes and conventional medical diagnosis delays the process of identifying cancer cells at the early stages. Clinical practices and diagnostic techniques need further enhancements in processing cancer images newline
Pagination: 
URI: http://hdl.handle.net/10603/305680
Appears in Departments:Department of Computer Science Engineering

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abstract.pdf33.26 kBAdobe PDFView/Open
acknowledgement.pdf24.81 kBAdobe PDFView/Open
chapter 1.pdf828.53 kBAdobe PDFView/Open
chapter 2.pdf459.4 kBAdobe PDFView/Open
chapter 3.pdf585.62 kBAdobe PDFView/Open
chapter 4.pdf1.1 MBAdobe PDFView/Open
chapter 5.pdf563.87 kBAdobe PDFView/Open
chapter 6.pdf246.59 kBAdobe PDFView/Open
declaration.pdf254.36 kBAdobe PDFView/Open
list of publications.pdf294.75 kBAdobe PDFView/Open
preliminary pages.pdf335.72 kBAdobe PDFView/Open
references.pdf536.66 kBAdobe PDFView/Open
title.pdf291.72 kBAdobe PDFView/Open
vitae.pdf184.01 kBAdobe PDFView/Open
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