Issue |
ITM Web Conf.
Volume 70, 2025
2024 2nd International Conference on Data Science, Advanced Algorithm and Intelligent Computing (DAI 2024)
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Article Number | 04030 | |
Number of page(s) | 7 | |
Section | AI and Advanced Applications | |
DOI | https://doi.org/10.1051/itmconf/20257004030 | |
Published online | 23 January 2025 |
Lung Cancer Prediction Based on K-nearest Neighbor and Other Algorithms
Jinan Foreign Language School, Jinan, 250000, China
Corresponding author: renhao@cha-tm.com
Lung cancer is still the most affected type of cancer in the world. The purpose of this study is to achieve a certain accuracy of lung cancer prediction based on a variety of computer algorithms, to effectively reduce the prevalence of cancer in the future. The computer algorithms mainly used in this paper include Random forest, K-nearest neighbours, and Logistic regression. By collecting lung cancer patients and clinical data sets, basic prediction is realized through programming code, and data visualization is finally realized to complete prediction. Finally, it is found that the prediction of lung cancer using a single variable is not accurate, and there are many factors leading to lung cancer. It is necessary to import as many data sets as possible to increase the reliability of prediction. The study found that smoking had the greatest impact on the risk of developing lung cancer. After the study in this paper, it is recommended that all people carry out a healthy life schedule, which can effectively prevent lung cancer. At the same time, the study found that the prediction of lung cancer by computer algorithm is achievable, and more algorithms can be combined to achieve higher precision prediction in the future.
© The Authors, published by EDP Sciences, 2025
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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