ArticleScientific reports2023
Visual field prediction using a deep bidirectional gated recurrent unit network model.
Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed.
- Future visual field prediction in glaucoma: an application of first-order autoregressive approach.International ophthalmology · 2026Article
- Comparing the Use of Measured and Smoothed Data in Forecasting Visual Field Tests Using Deep Learning.Ophthalmology science · 2026Article
- Predicting worsening visual field via masked dual stage attention recurrent neural network.Scientific reports · 2026Article
- Deep Learning-Based Prediction of Visual Field Mean Deviation from Numeric OCT Data in Glaucoma.Journal of imaging informatics in medicine · 2026Article
- A systematic review of AI for predicting glaucoma progression: challenges and recommendations towards clinical implementation.NPJ digital medicine · 2026Article
- Prediction of recovery grade in Bell's palsy using machine learning models.Scientific reports · 2026Article
- Functional generalized estimating equation model to detect glaucomatous visual field progression.International journal of ophthalmology · 2026Article
- Visual field prediction using K-means clustering in patients with primary open angle glaucoma.International journal of ophthalmology · 2026Article
- Bidirectional Long Short-Term Memory (BiLSTM) Neural Networks with Conjoint Fingerprints: Application in Predicting Skin-Sensitizing Agents in Natural Compounds.Journal of chemical information and modeling · 2025Article
- Artificial intelligence in traditional Chinese medicine: advances in multi-metabolite multi-target interaction modeling.Frontiers in pharmacology · 2025Review
- Advancements in Viral Genomics: Gated Recurrent Unit Modeling of SARS-CoV-2, SARS, MERS, and Ebola viruses.Revista da Sociedade Brasileira de Medicina Tropical · 2025Article
- RETRACTED: Hosni Mahmoud, H.A.; Alabdulkreem, E. Bidirectional Neural Network Model for Glaucoma Progression Prediction.Journal of personalized medicine · 2024Article
- Deep learning models to predict primary open-angle glaucoma.Stat (International Statistical Institute) · 2024Article
- Bidirectional gated recurrent unit network model can generate future visual field with variable number of input elements.PloS one · 2024Article
- A Hybrid Deep Learning-Based Approach for Visual Field Test Forecasting.Ophthalmology scienceArticle
- Application of artificial intelligence in glaucoma care: An updated review.Taiwan journal of ophthalmologyReview
- Big data in visual field testing for glaucoma.Taiwan journal of ophthalmologyReview
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Authors and funding
12 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Although deep learning architecture has been used to process sequential data, only a few studies have explored the usefulness of deep learning algorithms to detect glaucoma progression. Here, we proposed a bidirectional gated recurrent unit (Bi-GRU) algorithm to predict visual field loss. In total, 5413 eyes from 3321 patients were included in the training set, whereas 1272 eyes from 1272 patients were included in the test set. Data from five consecutive visual field examinations were used as input; the sixth visual field examinations were compared with predictions by the Bi-GRU. The performance of Bi-GRU was compared with the performances of conventional linear regression (LR) and long short-term memory (LSTM) algorithms. Overall prediction error was significantly lower for Bi-GRU than for LR and LSTM algorithms. In pointwise prediction, Bi-GRU showed the lowest prediction error among the three models in most test locations. Furthermore, Bi-GRU was the least affected model in terms of worsening reliability indices and glaucoma severity. Accurate prediction of visual field loss using the Bi-GRU algorithm may facilitate decision-making regarding the treatment of patients with glaucoma.
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