International Journal For Multidisciplinary Research

E-ISSN: 2582-2160   •   Impact Factor: 9.24

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

Call for Paper Volume 7, Issue 2 (March-April 2025) Submit your research before last 3 days of April to publish your research paper in the issue of March-April.
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Volume 7 Issue 2
March-April 2025

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Breast Cancer Detection Using Machine Learning

Author(s) Mr. Md. Shahbaz Hassan, Mr. Rishabh Kumar, Mr. Rohit Kumar Yadav
Country India
Abstract Cancer mortality remains a significant challenge in developing nations, despite various preventive measures. Some cancer types still lack effective treatments. Breast cancer, one of the most prevalent forms, relies heavily on early detection for successful treatment. Accurate diagnosis plays a crucial role in managing breast cancer. Numerous studies have explored methods for predicting breast tumor types. This study utilized breast cancer tumor data from Kaggle datasets forecast tumor types. The research employed data visualization and machine learning techniques, including logistic regression and Python were used to implement these techniques and visualizations. The research aimed to conduct a comparative analysis of data visualization and machine learning applications for breast cancer detection and diagnosis. The diagnostic performance of these applications was found to be comparable in identifying breast cancers. The study demonstrated that data visualization and machine learning techniques could significantly benefit the decision-making process in cancer detection. Various machine learning and data mining techniques were proposed for breast cancer detection. The logistic regression model, incorporating all features, yielded the highest classification accuracy at 98.1%. This approach showed improved accuracy performance, suggesting potential new avenues for breast cancer detection.
Keywords Breast Cancer, Dataset, CNN, KNN, Naïve Bayes, Random Forest, SVM, Logistic Regression
Field Computer > Data / Information
Published In Volume 7, Issue 2, March-April 2025
Published On 2025-04-19
DOI https://doi.org/10.36948/ijfmr.2025.v07i02.41964
Short DOI https://doi.org/g9f4zf
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E-ISSN 2582-2160
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