Lung Cancer Feature Analysis and Classification Prediction Based on Machine Learning and Deep Learning

DOI

10.2991/978-94-6463-540-9_8How to use a DOI?

Keywords

Classification prediction; Machine learning; Deep learning; Lung cancer

Abstract

In recent years, lung cancer has the highest number of confirmed cases and a high mortality rate among all types of cancer, thus, it is vital to make timely and accurate lung cancer predictions. To alleviate this situation, this paper experimented with lung cancer classification prediction based on historical data using machine learning (ML) and deep learning (DL) methods. The study uses correlation analysis and F-test to perform feature selection and feature merging on the dataset. Then, K-nearest Neighbour (KNN) and eXtreme Gradient Boosting (XGBoost) in ML and Convolutional Neural Networks (CNN) in DL are applied for the prediction, classifying people into three risk levels of being diagnosed with lung cancer. The result of this experiment shows that KNN performs the best in terms of runtime and XGBoost has the best interpretability. Also, features like “obesity”, “fatigue”, “coughing of blood,” and “air pollution” play a significant role in lung cancer classification. In contrast, others, including “age” and “gender” have little impact on the classification. This paper provides a possibility for screening potential patients with lung cancer, to some extent, alleviating the situation of delayed diagnosis of lung cancer due to limitations in existing medical technology.

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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TY  - CONF
AU  - Xin You
PY  - 2024
DA  - 2024/10/16
TI  - Lung Cancer Feature Analysis and Classification Prediction Based on Machine Learning and Deep Learning
BT  - Proceedings of the 2024 2nd International Conference on Image, Algorithms and Artificial Intelligence (ICIAAI 2024)
PB  - Atlantis Press
SP  - 60
EP  - 69
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-540-9_8
DO  - 10.2991/978-94-6463-540-9_8
ID  - You2024
ER  -