JOURNAL ARTICLE

Detection of Breast Cancer from Mammogram using Convolution Neural Network

Shubham ParulekarMihir GadkarMilind Paraye

Year: 2023 Journal:   International Journal for Research in Applied Science and Engineering Technology Vol: 11 (10)Pages: 1077-1083   Publisher: International Journal for Research in Applied Science and Engineering Technology (IJRASET)

Abstract

Abstract: Breast cancer is the leading cause of cancer among women. In the last few years, the number of cases of breast cancer has skyrocketed among younger women. Detection of breast cancer during the initial stages can greatly reduce the risk of fatality. Mammograms which are X-ray images of breast tissues are used extensively by doctors to determine the early onset of breast cancer. However, due to human error, a lack of resources and knowledge can result in inaccurate predictions which can prove fatal. The power of Artificial Intelligence to process and predict images has greatly increased in the past few years. Many modern medical devices utilize the power of sophisticated AI algorithms to aid in detecting and predicting the early onset of breast cancer. In this paper, we demonstrate how we can utilize a convolution neural network to predict the early onset of breast cancer and help solve the issue of inaccurate detection of cancer cells from mammogram images.

Keywords:
Breast cancer Artificial neural network Cancer Convolution (computer science) Computer science Artificial intelligence Medicine Mammography Internal medicine

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Topics

AI in cancer detection
Physical Sciences →  Computer Science →  Artificial Intelligence
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