conference-paper

Comparative Survey of Various Intelligent Methods for Breast Cancer Diagnosis and Prognosis

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Abstract

Cancer remains a major contributor to mortality rates across the globe, causing nearly 10 million fatalities in 2020. Among all cancer types, breast cancer has the highest incidence, around 2.26 million cases reported across the globe by the World Health Organization. In the last few years, breast cancer was diagnosed in approximately 2.3 million people and caused around 685,000 deaths. In this paper, our investigation entails executing a statistical scrutiny of the worldwide proliferation of breast cancer, as well as delving into various machine learning and deep learning techniques for detecting breast cancer, along with their constraints and intricacies. Additionally, we have proposed a hybrid Machine Learning (ML) approach for detecting breast cancer with utmost accuracy, which streamlines the assessment procedure presently employed by radiologists in screening mammograms.

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Publication details

DOI
10.1109/icccnt56998.2023.10307593
OpenAlex
W4388938404
Document type
conference-paper
Language
EN
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