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Breast Cancer Detection Using Machine Learning

Breast Cancer Detection Using Machine Learning Code, Document And Tutorial Video

breast cancer

Abstract:

Breast cancer is a leading cause of cancer-related deaths among women worldwide. Early detection is crucial for effective treatment and survival. This study proposes a machine learning-based approach for detecting breast cancer from mammography images. A comprehensive dataset of mammography images is used to train and evaluate the performance of various machine learning algorithms, including Convolutional Neural Networks (CNNs), Support Vector Machines (SVMs), and Random Forest. The results show that the proposed approach achieves high accuracy, precision, and recall rates, outperforming traditional computer-aided detection systems. The study demonstrates the potential of machine learning in improving the accuracy and efficiency of breast cancer detection, enabling early intervention and better treatment outcomes.

Keywords: Breast Cancer Detection, Machine Learning, Mammography Images, Convolutional Neural Networks, Support Vector Machines, Random Forest.

Project include:

  1. Synopsis

  2. PPT

  3. Research Paper

  4. Code

  5. Explanation video

  6. Documents

  7. Report

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