Proceedings of the 2024 International Conference on Artificial Intelligence and Communication (ICAIC 2024)

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Artificial Intelligence Model Selection for Breast Cancer Risk Screening

Authors
Ziwen Fang1, *
1Software Engineering, Lappeenranta-Lahti University of Technology(LUT), Yliopistonkatu 34, 53850, Lappeenranta, Finland
*Corresponding author. Email: Ziwen.Fang@student.lut.fi
Corresponding Author
Ziwen Fang
Available Online 23 September 2024.
DOI
10.2991/978-94-6463-512-6_64How to use a DOI?
Keywords
Artificial Intelligence; Machine Learning; Breast Cancer Risk Screening
Abstract

In today's social environment, the risk of breast cancer for women is increasing, and breast cancer has exceeded lung cancer as the most common cancer nowadays. However, if detect breast cancer at an early stage and measures are taken, it can be very effective in improving the chances of survival of breast cancer patients. Meanwhile, with the continuous development of artificial intelligence, it shows a broad prospect in the medical field. In this article experiment try to apply AI to the field of breast cancer risk detection, and help improve the accuracy of breast cancer screening by finding the artificial intelligence model with the highest accuracy rate. This article selected breast cancer data from kaggle, pre-processed the data by Pearson Correlation Coefficient, and then the article compares four of the most common machine learning algorithms namely Random Forest, Logistic Regression, Neural Networks, and Support Vector Machines, using Python. Based on the experimental results the article conclude that Random Forest is highly accurate and shows great affect in the field of breast cancer screening.

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 International Conference on Artificial Intelligence and Communication (ICAIC 2024)
Series
Advances in Intelligent Systems Research
Publication Date
23 September 2024
ISBN
978-94-6463-512-6
ISSN
1951-6851
DOI
10.2991/978-94-6463-512-6_64How 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

risenwbib
TY  - CONF
AU  - Ziwen Fang
PY  - 2024
DA  - 2024/09/23
TI  - Artificial Intelligence Model Selection for Breast Cancer Risk Screening
BT  - Proceedings of the 2024 International Conference on Artificial Intelligence and Communication (ICAIC 2024)
PB  - Atlantis Press
SP  - 606
EP  - 618
SN  - 1951-6851
UR  - https://doi.org/10.2991/978-94-6463-512-6_64
DO  - 10.2991/978-94-6463-512-6_64
ID  - Fang2024
ER  -