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A Comparative study of Breast Cancer Diagnosis and Classification Using Neural Networks and Machine learning models

Dubey, Sakshi (2022) A Comparative study of Breast Cancer Diagnosis and Classification Using Neural Networks and Machine learning models. Masters thesis, Dublin, National College of Ireland.

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Abstract

Over the time period, the rise in incidence and mortality rates due to deaths caused from breast cancer is evident that it’s turning a terminal disease globally. An early detection of these developments in the female body can reduce the risk of cancer spreading throughout the body and expensive treatment costs. Early diagnosis and modern cancer treatment is essential for better understanding of development of cancerous tissues in the female breast and most importantly prevent deaths from cancer. Hence, it is essential to develop a robust system for early-stage breast cancer diagnosis that can assist the medical professionals to classify cancer tissues in mammograms and thus save lives of patients. In this research, we are implementing nine machine learning algorithms and one artificial neural network model on “Wisconsin Breast cancer” dataset to determine the presence of cancer and classify the type of abnormality as benign and malignant. The primary objective of our research is implementing machine learning and deep learning algorithms on trained data and detect and classify the severity of cancer through effective exploratory data analysis, feature selection and performance metrics of classification models. We intend to provide a robust and reliable approach for early-stage diagnosis of breast cancer using machine learning and deep learning methodologies so there can be enough space for treatment plans and higher chances of survival in patients.

Item Type: Thesis (Masters)
Uncontrolled Keywords: Breast cancer; machine learning; deep learning; malignant; benign
Subjects: Q Science > QA Mathematics > Electronic computers. Computer science
T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science
T Technology > Biomedical engineering
Q Science > Life sciences > Medical sciences > Pathology > Tumors > Cancer
Q Science > Q Science (General) > Self-organizing systems. Conscious automata > Machine learning
Divisions: School of Computing > Master of Science in Data Analytics
Depositing User: Tamara Malone
Date Deposited: 24 Jan 2023 12:35
Last Modified: 03 Mar 2023 13:00
URI: https://norma.ncirl.ie/id/eprint/6113

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