Breast Cancer Detection using Machine Learning

Author(s)	Samarth Kumar, Simar Ahuja, Shobha Rekh
Country	India
Abstract	Breast cancer is one of the worst cancer diseases in the world which affects a very large number of people. Detecting and diagnosing this disease early is vital, since it is crucial for the survival of the patient. The main objective of this study is to investigate the different technologies that are used for identifying and diagnosing breast cancers. Furthermore, it explores different machine learning approaches, computer-aided detection systems (CAD) and common medical treatments used to diagnose and treat these fatal diseases on a higher level. Also, there is a difference between commercial software and tools that are used for identifying and assessing all stages of breast cancer against tools and software that are provided by nonprofit organizations. The conclusion of this report is that there is no method or standardized procedure to identify and diagnose breast cancer using all technologies.
Keywords	Breast Cancer, Dataset, CNN, KNN, Naïve Bayes, Random Forest, SVM, Logistic Regression.
Field	Computer
Published In	Volume 6, Issue 3, May-June 2024
Published On	2024-06-25
Cite This	Breast Cancer Detection using Machine Learning - Samarth Kumar, Simar Ahuja, Shobha Rekh - IJFMR Volume 6, Issue 3, May-June 2024. DOI 10.36948/ijfmr.2024.v06i03.23223
DOI	https://doi.org/10.36948/ijfmr.2024.v06i03.23223
Short DOI	https://doi.org/gt2432

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International Journal For Multidisciplinary Research