Manuscript Number : IJSRSET2310375

A Breast Cancer Diagnosis Framework Based on Machine Learning

Authors(5) :-Dr. Nikhat Akhtar, Dr. Hemlata Pant, Apoorva Dwivedi, Vivek Jain, Dr. Yusuf Perwej

Breast cancer is becoming the leading cause of mortality among women. One of the most prevalent diseases in women, breast cancer is brought on by a variety of clinical, lifestyle, social, and economic variables. Predictive approaches based on machine learning offer methods for diagnosing breast cancer sooner. It may be found using a variety of analytical methods, including Breast MRI, X-ray, thermography, mammograms, ultrasound, etc. The most prevalent technique for performance evaluation uses accuracy measures, and the Convolutional Neural Network (CNN) is the most accurate and widely used model for breast cancer diagnosis. The Wisconsin Breast Cancer Datasets (WBCD) were used to evaluate the suggested method. Out of a total of 569 samples, 273 samples were chosen for this experiment as the test data, while the other samples were utilized for training and validation. The review's findings showed that the Convolutional Neural Network (CNN) is the most effective and widely used model for finding breast cancer, and that the most often used technique for judging performance is accuracy metrics. The application of deep learning to such a wide range of real-world issues is astounding.

Authors and Affiliations

Dr. Nikhat Akhtar
Associate Professor, Department of Computer Science & Engineering, Ambalika Institute of Management & Technology, Lucknow, Uttar Pradesh, India
Dr. Hemlata Pant
Associate Professor, Department of Computer Science & Engineering, Ambalika Institute of Management & Technology, Lucknow, Uttar Pradesh, India
Apoorva Dwivedi
Assistant Professor, Department of Computer Science & Engineering, Ambalika Institute of Management & Technology, Lucknow, Uttar Pradesh, India
Vivek Jain
Professor, Department of Computer Science & Engineering, IMS Engineering College, Ghaziabad, Uttar Pradesh, India
Dr. Yusuf Perwej
Assistant Professor, Department of Computer Science & Engineering, Ambalika Institute of Management & Technology, Lucknow, Uttar Pradesh, India

Machine Learning, Breast Cancer, Malignant, Classification, Convolutional Neural Network (CNN), Wisconsin Breast Cancer Datasets (WBCD), UCI Machine Learning Repository.

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Publication Details

Published in : Volume 10 | Issue 3 | May-June 2023
Date of Publication : 2023-06-30
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 118-132
Manuscript Number : IJSRSET2310375
Publisher : Technoscience Academy

Print ISSN : 2395-1990, Online ISSN : 2394-4099

Cite This Article :

Dr. Nikhat Akhtar, Dr. Hemlata Pant, Apoorva Dwivedi, Vivek Jain, Dr. Yusuf Perwej, " A Breast Cancer Diagnosis Framework Based on Machine Learning, International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 10, Issue 3, pp.118-132, May-June-2023. Available at doi : https://doi.org/10.32628/IJSRSET2310375      Journal URL : https://res.ijsrset.com/IJSRSET2310375

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