Convolutional Neural Networks for Predictive Modeling of Lung Disease

Haohao Xia; Xiqing Liu; Yingbin Liang; Yiru Cang; Yuanfang Yang; Zitao Zheng

REVIEW

Convolutional Neural Networks for Predictive Modeling of Lung Disease

Not yet reviewed by Pith; the record is open.

Re-run · record.json Download PDF Read on arXiv ↗

This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.

SPECIMEN: schema-true, not a live event

T0 review · schema-true

One-sentence machine reading of the paper's core claim.

pith:XXXXXXXX · record.json · timestamp

arxiv 2408.12605 v1 pith:TOWV47C2 submitted 2024-08-08 eess.IV cs.AIcs.CV

Convolutional Neural Networks for Predictive Modeling of Lung Disease

Yingbin Liang , Xiqing Liu , Haohao Xia , Yiru Cang , Zitao Zheng , Yuanfang Yang This is my paper

classification eess.IV cs.AIcs.CV

keywords accuracydiseaseinnovativelungmodelpro-hrnet-cnnauthoritativeavenue

verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved

0 comments

read the original 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.

Convolutional Neural Networks for Predictive Modeling of Lung Disease

discussion (0)