Ruiwen Zhou, J. Philip Miller, Mae Gordon, Michael Kass, Mingquan Lin, Yifan Peng, Fuhai Li, Jiarui Feng, Lei Liu
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Deep learning models to predict primary open-angle glaucoma
Glaucoma is a major cause of blindness and vision impairment worldwide, and visual field (VF) tests are essential for monitoring the conversion of glaucoma. While previous studies have primarily focused on using VF data at a single time point for glaucoma prediction, there has been limited exploration of longitudinal trajectories. Additionally, many deep learning techniques treat the time-to-glaucoma prediction as a binary classification problem (glaucoma Yes/No), resulting in the misclassification of some censored subjects into the nonglaucoma category and decreased power. To tackle these challenges, we propose and implement several deep-learning approaches that naturally incorporate temporal and spatial information from longitudinal VF data to predict time-to-glaucoma. When evaluated on the Ocular Hypertension Treatment Study (OHTS) dataset, our proposed convolutional neural network (CNN)-long short-term memory (LSTM) emerged as the top-performing model among all those examined. The implementation code can be found online (https://github.com/rivenzhou/VF_prediction).
StatDecision Sciences-Statistics, Probability and Uncertainty
CiteScore
1.10
自引率
0.00%
发文量
85
期刊介绍:
Stat is an innovative electronic journal for the rapid publication of novel and topical research results, publishing compact articles of the highest quality in all areas of statistical endeavour. Its purpose is to provide a means of rapid sharing of important new theoretical, methodological and applied research. Stat is a joint venture between the International Statistical Institute and Wiley-Blackwell.
Stat is characterised by:
• Speed - a high-quality review process that aims to reach a decision within 20 days of submission.
• Concision - a maximum article length of 10 pages of text, not including references.
• Supporting materials - inclusion of electronic supporting materials including graphs, video, software, data and images.
• Scope - addresses all areas of statistics and interdisciplinary areas.
Stat is a scientific journal for the international community of statisticians and researchers and practitioners in allied quantitative disciplines.