Lung Cancer Prediction Based on Lightweight Neural Networks

As lung cancer is becoming one of the major causes of death, early detection is increasingly needed. In this study, we propose a lightweight neural network to predict lung cancer using clinical and lifestyle features, encoded from A dataset comprising 5000 samples. Our model achieves an accuracy of...

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Bibliographic Details
Published in2025 IEEE 2nd International Conference on Deep Learning and Computer Vision (DLCV) pp. 1 - 5
Main Authors Liu, Zhiyan, Zhang, Yongzhen, Tang, Enyu, Ouyang, Yuqi
Format Conference Proceeding
LanguageEnglish
Published IEEE 06.06.2025
Subjects
Accuracy
Computational modeling
Deep learning
Imaging
Lung cancer
Machine Learning
Medical diagnosis
MLP
Neural networks
Prediction
Predictive models
Random forests
Support vector machines
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DOI10.1109/DLCV65218.2025.11088848

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Summary:As lung cancer is becoming one of the major causes of death, early detection is increasingly needed. In this study, we propose a lightweight neural network to predict lung cancer using clinical and lifestyle features, encoded from A dataset comprising 5000 samples. Our model achieves an accuracy of \mathbf{9 2 \%} . These results illustrate the potential of deep learning methods in supporting early diagnosis of lung cancer.
DOI:10.1109/DLCV65218.2025.11088848