Early Breast Cancer Prediction using Machine Learning and Deep Learning Techniques

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Published: Oct 7, 2023
DOI: https://doi.org/10.17762/ijritcc.v11i10s.7603
Keywords:
Breast Cancer, Machine Learning, XGB Classifier, Decision Tree, Naïve Bayes, Logistic Regression, Support Vector Machine, Random Forest, Deep Learning, Artificial Neural Network

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Swati B. Patil
Department of Computer Engineering Vishawakarma Institute of Information Technology Pune, India
Ritesh V. Patil
Department of Computer Engineering PEDA’s College Of Engineering, Manjari(BK) Research Guide Department of Computer Engineering Vishawakarma Institute of Information Technology Pune, India
Parikshit N. Mahalle
Department of Computer Engineering Vishawakarma Institute of Information Technology Pune, India

Abstract

Breast Cancer (BC) is a considered as one of the utmost lethal diseases across the globe that has a very high morbidity and mortality rate. Accurate and early prediction along with diagnosis is one of the most crucial characteristics for the treatment of Breast Cancer. Doctors can have an edge over Breast cancer if they are able to predict it in its early stages using deep learning and machine learning techniques. This paper proposed consists of comparison between the and accuracy of various machine learning models like Support vector machine (SVM), K-Nearest Neighbours (KNN), Naïve Bayes (NB), Logistic Regression (LR), Random Forest (RF), Decision Tree (DT), XGB Classifier and deep learning model of Artificial neural networks (ANN) for the precise detection of breast cancer.


The most crucial properties from the database have been chosen using one feature-selection technique. Correlation is also used to choose the most correlated features from the data. Implementing the ANN model consists of one input layer, two hidden layers, and one output layer. All Machine Learning models and ANN model are then applied to selected features. The results demonstrated that the SVM classifier achieved the highest performance with an accuracy of ~98.24%.

Article Details

How to Cite
Patil, S. B. ., Patil, R. V. ., & Mahalle, P. N. . (2023). Early Breast Cancer Prediction using Machine Learning and Deep Learning Techniques. International Journal on Recent and Innovation Trends in Computing and Communication, 11(10s), 111–117. https://doi.org/10.17762/ijritcc.v11i10s.7603
Issue
Vol. 11 No. 10s (2023)
Section
Articles

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