Machine Learning and Deep Learning Techniques for Classification of Breast Cancer: A Survey

Karthikeya Mallelli; Bharath Kumar Nangunuri; Sathupati Vaishnavi; Greshma Neredimelli; Talupula Vaishnavi

doi:10.36948/ijfmr.2024.v06i03.22929

Machine Learning and Deep Learning Techniques for Classification of Breast Cancer: A Survey

Author(s)	Karthikeya Mallelli, Bharath Kumar Nangunuri, Sathupati Vaishnavi, Greshma Neredimelli, Talupula Vaishnavi
Country	India
Abstract	One of the main causes of death is breast cancer or BC. With this survey paper, people can understand what is breast cancer, how it causes death, and what treatments can be used to diagnose breast cancer. Accurate categorization of breast cancer data is essential for cancer diagnosis, and the ability to distinguish benign from malignant tumors can save patients unnecessary medical interventions. The optimal course of action can also be determined using the classification of breast cancer. One well-known area of medical research is the classification of patient populations into benign and malignant conditions. Because machine learning can extract significant characteristics from a collection of medical data, it is widely used in the prediction of breast cancer. Machine learning methods in medical diagnostics have drawn increased interest lately. These technologies, along with the many deep learning approaches that have surfaced recently, allow information based solely on gene expression to be used to inform healthcare decisions, offering insight into sound and suitable healthcare decisions. Tissue texture and breast density are commonly used by doctors and automated technologies as indicators of sickness in diagnostic imaging. Customized screening and preventive decisions can be guided by the exact identification of cancer risk. So, by analyzing this paper people can understand how breast cancer can be detected using machine learning and deep learning techniques and what these techniques make special rather than manual identifying of breast cancer, also it includes different research paper surveys that many professional authors have done. Convolutional neural networks (CNNs) are being used in deep learning to tackle a range of classification and prediction tasks, including breast imaging like Long Short Term Memory(LSTM) and Recurrent Neural Network(RNN) networks.
Keywords	Deep Learning; Convolutional Neural Network(CNN);Long Short Term Memory(LSTM); Recurrent Neural Network(RNN); Classification; Diagnosis; Imaging
Field	Medical / Pharmacy
Published In	Volume 6, Issue 3, May-June 2024
Published On	2024-06-17
Cite This	Machine Learning and Deep Learning Techniques for Classification of Breast Cancer: A Survey - Karthikeya Mallelli, Bharath Kumar Nangunuri, Sathupati Vaishnavi, Greshma Neredimelli, Talupula Vaishnavi - IJFMR Volume 6, Issue 3, May-June 2024. DOI 10.36948/ijfmr.2024.v06i03.22929
DOI	https://doi.org/10.36948/ijfmr.2024.v06i03.22929
Short DOI	https://doi.org/gt2bxb

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Machine Learning and Deep Learning Techniques for Classification of Breast Cancer: A Survey

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