Proceedings of the 2024 2nd International Conference on Image, Algorithms and Artificial Intelligence (ICIAAI 2024)

The Investigation on Breast Cancer Prediction Technologies Based on Machine Learning Algorithms

Authors
Qinzheng Luo1, *
1Robotics and Intelligent Devices, Fuzhou University, Fuzhou, 350000, China
*Corresponding author. Email: 1809020205@stu.hrbust.edu.cn
Corresponding Author
Qinzheng Luo
Available Online 16 October 2024.
DOI
10.2991/978-94-6463-540-9_4How to use a DOI?
Keywords
Breast Cancer Prediction; Artificial Neural Network; Convolutional Neural Network
Abstract

As one of the most common types of cancer in women in the world and early diagnosis of breast cancer is crucial to improve the survival rate and quality of life of patients worldwide. Therefore, it is of great significance to develop efficient and accurate breast cancer prediction methods for the medical field. This paper aims to explore the breast cancer prediction methods based on machine learning, especially the application of Artificial Neural Network (ANN) and Convolutional Neural Network (CNN) in breast cancer diagnosis. In the research method, this paper introduces two kinds of breast cancer prediction methods based on machine learning. The first method is to construct a multi-layer perceptron model by using Artificial Neural Network (ANN) and optimize the network structure by using Back Propagation algorithm to realize automatic classification of mammography images. The second method uses Convolutional Neural Network (CNN), combined with a weighted Fisher algorithm and deep learning technology, to further improve the accuracy of breast cancer prediction. The research results show that the breast cancer prediction method based on machine learning has reached a high level in accuracy, sensitivity and specificity, and provides a new and effective means for early detection and diagnosis of breast cancer. The breast cancer prediction method based on machine learning proposed in this paper has important application value in the medical field, not only can improve the accuracy and efficiency of breast cancer prediction, but also can provide more timely and effective treatment suggestions for patients.

Copyright
© 2024 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 2024 2nd International Conference on Image, Algorithms and Artificial Intelligence (ICIAAI 2024)
Series
Advances in Computer Science Research
Publication Date
16 October 2024
ISBN
978-94-6463-540-9
ISSN
2352-538X
DOI
10.2991/978-94-6463-540-9_4How to use a DOI?
Copyright
© 2024 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

TY  - CONF
AU  - Qinzheng Luo
PY  - 2024
DA  - 2024/10/16
TI  - The Investigation on Breast Cancer Prediction Technologies Based on Machine Learning Algorithms
BT  - Proceedings of the 2024 2nd International Conference on Image, Algorithms and Artificial Intelligence (ICIAAI 2024)
PB  - Atlantis Press
SP  - 27
EP  - 34
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-540-9_4
DO  - 10.2991/978-94-6463-540-9_4
ID  - Luo2024
ER  -