Convolutional Neural Networks for Predictive Modeling of Lung Disease
<|reference_start|>Convolutional Neural Networks for Predictive Modeling of Lung Disease: In this paper, Pro-HRnet-CNN, an innovative model combining HRNet and void-convolution techniques, is proposed for disease prediction under lung imaging. Through the experimental comparison on the authoritative LIDC-IDRI dataset, we found that compared with the traditional ResNet-50, Pro-HRnet-CNN showed better performance in the feature extraction and recognition of small-size nodules, significantly improving the detection accuracy. Particularly within the domain of detecting smaller targets, the model has exhibited a remarkable enhancement in accuracy, thereby pioneering an innovative avenue for the early identification and prognostication of pulmonary conditions.<|reference_end|>
@article{liang2024convolutional,
    title={Convolutional Neural Networks for Predictive Modeling of Lung Disease},
    author={Yingbin Liang, Xiqing Liu, Haohao Xia, Yiru Cang, Zitao Zheng,
  Yuanfang Yang},
    journal={arXiv preprint arXiv:2408.12605},
    year={2024},
    archivePrefix={arXiv},
    eprint={2408.12605},
    primaryClass={eess.IV cs.AI cs.CV}
}