Detection and Categorization of Breast Cancer Using Machine Learning

Cancer that originates in the breast tissue is known as breast cancer. A breast lump, breast form changes, skin dimpling, fluid flowing from the nipple, a newly inverted nipple, or a red or scaly patch of skin can all be indicators of breast cancer. Yellow skin, shortness of breath, enlarged lymph n...

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Bibliographic Details
Published in:	2024 10th International Conference on Communication and Signal Processing (ICCSP) pp. 260 - 264
Main Authors:	Parvatham, N, Saye Sudharsana, P A, Lavanya, E, Savithavani, A
Format:	Conference Proceeding
Language:	English
Published:	IEEE 12-04-2024
Subjects:	Benign Breast cancer Breast Cancer detection Fluids Histopathology Machine learning Malignant Medical diagnostic imaging Pain Signal processing Skin
Online Access:	Get full text
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Summary:	Cancer that originates in the breast tissue is known as breast cancer. A breast lump, breast form changes, skin dimpling, fluid flowing from the nipple, a newly inverted nipple, or a red or scaly patch of skin can all be indicators of breast cancer. Yellow skin, shortness of breath, enlarged lymph nodes, and bone pain are possible symptoms in those whose disease has progressed far. The initial goal is to examine the different deep learning models for image classification of breast cancer histology. According to research, the majority of skilled medical professionals can identify cancer with 79% accuracy, however machine learning approaches can obtain a 91% right diagnosis. Delaying the growth of a tumor or breast cancer has long-term consequences and may even be fatal. Therefore, it is important to detect the tumor as soon as possible in order to stop its growth and stop it from spreading to other tissues. It is typically recommended to undergo a mammography procedure in order to detect and diagnose breast cancer early.
ISSN:	2836-1873
DOI:	10.1109/ICCSP60870.2024.10543436