Comparative performance of deep learning architectures for diabetic peripheral neuropathy detection using corneal confocal microscopy: a retrospective single-centre study

The InceptionV3-based DLA model achieved superior performance compared with traditional convolutional neural network architectures like ResNet and DenseNet, and the Swin transformer model, highlighting its potential for effective DPN screening.

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Publication Details

Journal
BMJ Open
Published
2025-08-01
DOI
https://doi.org/10.1136/bmjopen-2024-095342
Citations
1
Primary Topic
Retinal Imaging and Analysis
Type
article
Field-Weighted Citation Impact
1.36
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article

Comparative performance of deep learning architectures for diabetic peripheral neuropathy detection using corneal confocal microscopy: a retrospective single-centre study

Jianzhang Hu, Yuyang Deng, Woei‐Luen Chen, Weihuang Xu
1 citations
BMJ Open
Retinal Imaging and Analysis
1.36
article

Comparative performance of deep learning architectures for diabetic peripheral neuropathy detection using corneal confocal microscopy: a retrospective single-centre study

Jianzhang Hu, Yuyang Deng, Woei‐Luen Chen, Weihuang Xu
article en
1 citations

Abstract

The InceptionV3-based DLA model achieved superior performance compared with traditional convolutional neural network architectures like ResNet and DenseNet, and the Swin transformer model, highlighting its potential for effective DPN screening.

BMJ OpenVol. 15(8)
Fujian Medical University (CN), Union Hospital (CN)
Openalex Percentile: Top 17%
Retinal Imaging and Analysis
1.36
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