ROPRNet: Deep learning-assisted recurrence prediction for retinopathy of prematurity

•ROPRNet: a dual-modal model for recurrence prediction of retinopathy of prematurity.•Corrected gestational age at treatment is involved as a key factor for prediction.•ROPRNet uses dual-modal ROP data for prediction, i.e. fundus images and risk factors.•Enhanced ConvNeXt is designed with ATBA and R...

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Bibliographic Details

Published in:	Biomedical signal processing and control Vol. 100; p. 107135
Main Authors:	Huang, Peijie, Xie, Yiying, Wu, Rong, Lin, Qiuxia, Cai, Nian, Chen, Haitao, Feng, Songfu
Format:	Journal Article
Language:	English
Published:	Elsevier Ltd 01.02.2025
Subjects:	Adaptive triple-branch attention Dual-Modal deep learning Multi-dimensional multi-scale feature fusion Recurrence prediction Retinopathy of prematurity Recurrence prediction Retinopathy of prematurity Multi-dimensional multi-scale feature fusion Dual-Modal deep learning Adaptive triple-branch attention
ISSN:	1746-8094
Online Access:	Get full text
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