Convolutional Neural Networks for Predictive Modeling of Lung Disease

• URL: http://arxiv.org/abs/2408.12605v1
• Date: Thu, 8 Aug 2024 01:58:46 GMT
• Title: Convolutional Neural Networks for Predictive Modeling of Lung Disease
• Authors: Yingbin Liang, Xiqing Liu, Haohao Xia, Yiru Cang, Zitao Zheng, Yuanfang Yang,
• Abstract summary: Pro-HRnet-CNN is an innovative model combining HRNet and void-convolution techniques. Compared with the traditional ResNet-50, Pro-HRnet-CNN showed better performance in the feature extraction and recognition of small-size nodules.
• Score: 34.1086022278394
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: 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.

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