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Public Health Genomics and Precision Health Knowledge Base (v9.0)
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Precision Health Database|Search|Public Health Genomics and Precision Health Knowledge Base (PHGKB)
Last data update: Apr 25, 2024
. (Total: 63675 Documents since 2012)
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Advancements in Glaucoma Diagnosis: The Role of AI in Medical Imaging.
Clerimar Paulo Bragança et al. Diagnostics (Basel) 2024 14(5)
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Prediction Models for Glaucoma in a Multicenter Electronic Health Records Consortium: The Sight Outcomes Research Collaborative.
Sophia Y Wang et al. Ophthalmol Sci 2024 4(3) 100445
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Artificial intelligence for glaucoma: state of the art and future perspectives.
Rafael Correia Barão et al. Curr Opin Ophthalmol 2023
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Comparing Active Surveillance and Watchful Waiting With Radical Treatment Using Machine Learning Models Among Patients With Prostate Cancer.
Siqi Hu et al. JCO Clin Cancer Inform 2023 7e2300083
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Smartphone Eye Examination: Artificial Intelligence and Telemedicine.
Manuel Augusto Pereira Vilela et al. Telemed J E Health 2023
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Artificial intelligence for home monitoring devices.
Tiarnan D L Keenan et al. Curr Opin Ophthalmol 2023
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Efficacy of deep learning-based artificial intelligence models in screening and referring patients with diabetic retinopathy and glaucoma.
Janani Surya et al. Indian J Ophthalmol 2023 71(8) 3039-3045
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Review of Visualization Approaches in Deep Learning Models of Glaucoma.
Byoungyoung Gu et al. Asia Pac J Ophthalmol (Phila) 2023 12(4) 392-401
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Review of Visualization Approaches in Deep Learning Models of Glaucoma.
Byoungyoung Gu et al. Asia Pac J Ophthalmol (Phila) 2023
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A generalizable deep learning regression model for automated glaucoma screening from fundus images.
Ruben Hemelings et al. NPJ Digit Med 2023 6(1) 112
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Clinical Applications of Artificial Intelligence in Glaucoma.
Siamak Yousefi et al. Journal of ophthalmic & vision research 2023 18(1) 97-112
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Implementation of deep learning artificial intelligence in vision-threatening disease screenings for an underserved community during COVID-19.
Aretha Zhu et al. Journal of telemedicine and telecare 2023 1357633X231158832
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Usability and Clinician Acceptance of a Deep Learning-Based Clinical Decision Support Tool for Predicting Glaucomatous Visual Field Progression.
Jimmy S Chen et al. Journal of glaucoma 2023 32(3) 151-158
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Reverse translation of artificial intelligence in glaucoma: Connecting basic science with clinical applications.
Da Ma et al. Frontiers in ophthalmology 2023 2
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Tele-Glaucoma Using a New Smartphone-based Tool for Visual Field Assessment.
Elisabeth Grau et al. Journal of glaucoma 2023
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Agreement of a Novel Artificial Intelligence Software with Optical Coherence Tomography and Manual Grading of the Optic Disc in Glaucoma.
Sujani Shroff et al. Journal of glaucoma 2023
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Geometric Deep Learning to Identify the Critical 3D Structural Features of the Optic Nerve Head for Glaucoma Diagnosis.
Braeu Fabian A et al. American journal of ophthalmology 2023
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Deep-Learning-Aided Diagnosis of Diabetic Retinopathy, Age-Related Macular Degeneration, and Glaucoma Based on Structural and Angiographic OCT.
Zang Pengxiao et al. Ophthalmology science 2022 3(1) 100245
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Precision medicine and glaucoma management: how mathematical modeling and artificial intelligence help in clinical practice.
Guidoboni G et al. Expert review of ophthalmology 2022 17(5) 299-301
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Glaucoma Detection and Classification Using Improved U-Net Deep Learning Model.
Kashyap Ramgopal et al. Healthcare (Basel, Switzerland) 2022 10(12)
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Deep Learning Approaches for Predicting Glaucoma Progression Using Electronic Health Records and Natural Language Processing.
Wang Sophia Y et al. Ophthalmology science 2022 2(2) 100127
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Smart soft contact lenses for continuous 24-hour monitoring of intraocular pressure in glaucoma care
J Zhang et al, Nat Comms, September 20, 2022
Automatic detection of glaucoma via fundus imaging and artificial intelligence: A review.
Coan Lauren et al. Survey of ophthalmology 2022
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Investigation of the Role of Convolutional Neural Network Architectures in the Diagnosis of Glaucoma using Color Fundus Photography.
Atalay Eray et al. Turkish journal of ophthalmology 2022 52(3) 193-200
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An Objective and Easy-to-Use Glaucoma Functional Severity Staging System Based on Artificial Intelligence.
Huang Xiaoqin et al. Journal of glaucoma 2022
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Identifying Those at Risk of Glaucoma: A Deep Learning Approach for Optic Disc and Cup Segmentation and Their Boundary Analysis.
Kim Jongwoo et al. Diagnostics (Basel, Switzerland) 2022 12(5)
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Deep Learning for Glaucoma Detection and Identification of Novel Diagnostic Areas in Diverse Real-World Datasets.
Noury Erfan et al. Translational vision science & technology 2022 11(5) 11
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An empirical study of preprocessing techniques with convolutional neural networks for accurate detection of chronic ocular diseases using fundus images.
Mayya Veena et al. Applied intelligence (Dordrecht, Netherlands) 2022 1-19
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Artificial Intelligence for Screening of Multiple Retinal and Optic Nerve Diseases.
Dong Li et al. JAMA network open 2022 5(5) e229960
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Detecting Glaucoma in the Ocular Hypertension Study Using Deep Learning.
Fan Rui et al. JAMA ophthalmology 2022
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Page last reviewed:
Feb 1, 2024
Page last updated:
Apr 25, 2024
Content source:
Public Health Genomics Branch in the Division of Blood Disorders and Public Health Genomics
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National Center on Birth Defects and Developmental Disabilities
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