deep learning – Computational Ophthalmology http://comp.ophthalmology.uw.edu/ big data. machine learning. data science. Fri, 17 Mar 2023 15:59:19 +0000 en-US hourly 1 https://wordpress.org/?v=5.6 Training Deep Learning Models to Work on Multiple Devices by Cross-Domain Learning with No Additional Annotations https://comp.ophthalmology.uw.edu/2023/03/17/training-deep-learning-models-to-work-on-multiple-devices-by-cross-domain-learning-with-no-additional-annotations/ Fri, 17 Mar 2023 15:59:19 +0000 https://comp.ophthalmology.uw.edu/?p=1362 Continue reading "Training Deep Learning Models to Work on Multiple Devices by Cross-Domain Learning with No Additional Annotations"

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Policy-Driven, Multimodal Deep Learning for Predicting Visual Fields from the Optic Disc and OCT Imaging https://comp.ophthalmology.uw.edu/2022/08/25/policy-driven-multimodal-deep-learning-for-predicting-visual-fields-from-the-optic-disc-and-oct-imaging/ Thu, 25 Aug 2022 23:10:37 +0000 https://comp.ophthalmology.uw.edu/?p=1322 Continue reading "Policy-Driven, Multimodal Deep Learning for Predicting Visual Fields from the Optic Disc and OCT Imaging"

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Application of deep learning to understand resilience to Alzheimer's disease pathology https://comp.ophthalmology.uw.edu/2021/05/19/application-of-deep-learning-to-understand-resilience/ Wed, 19 May 2021 00:35:00 +0000 https://comp.ophthalmology.uw.edu/?p=1156 Continue reading "Application of deep learning to understand resilience to Alzheimer's disease pathology"

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Using Deep Learning to Automate Goldmann Applanation Tonometry Readings https://comp.ophthalmology.uw.edu/2020/04/25/using-deep-learning-to-automate-goldmann-applanation-tonometry-readings/ Sat, 25 Apr 2020 23:08:00 +0000 http://faculty.washington.edu/leeay/wordpress/?p=363 Methodological Challenges of Deep Learning in Optical Coherence Tomography for Retinal Diseases: A Review https://comp.ophthalmology.uw.edu/2020/02/16/methodological-challenges-of-deep-learning-in-optical-coherence-tomography-for-retinal-diseases-a-review/ Sun, 16 Feb 2020 00:25:00 +0000 http://faculty.washington.edu/leeay/wordpress/?p=561 Data-Driven, Feature-Agnostic Deep Learning vs Retinal Nerve Fiber Layer Thickness for the Diagnosis of Glaucoma https://comp.ophthalmology.uw.edu/2020/02/13/data-driven-feature-agnostic-deep-learning-vs-retinal-nerve-fiber-layer-thickness-for-the-diagnosis-of-glaucoma/ Thu, 13 Feb 2020 00:25:00 +0000 http://faculty.washington.edu/leeay/wordpress/?p=360 Continue reading "Data-Driven, Feature-Agnostic Deep Learning vs Retinal Nerve Fiber Layer Thickness for the Diagnosis of Glaucoma"

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Validation of automated artificial intelligence segmentation of optical coherence tomography images https://comp.ophthalmology.uw.edu/2019/08/16/validation-of-automated-artificial-intelligence-segmentation-of-optical-coherence-tomography-images/ Fri, 16 Aug 2019 18:16:00 +0000 http://faculty.washington.edu/leeay/wordpress/?p=150 Continue reading "Validation of automated artificial intelligence segmentation of optical coherence tomography images"

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Forecasting future Humphrey Visual Fields using deep learning https://comp.ophthalmology.uw.edu/2019/04/14/forecasting-future-humphrey-visual-fields-using-deep-learning/ Sun, 14 Apr 2019 23:35:23 +0000 http://faculty.washington.edu/leeay/wordpress/?p=189 Continue reading "Forecasting future Humphrey Visual Fields using deep learning"

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Generating retinal flow maps from structural optical coherence tomography with artificial intelligence https://comp.ophthalmology.uw.edu/2019/04/05/generating-retinal-flow-maps-from-structural-optical-coherence-tomography-with-artificial-intelligence/ Fri, 05 Apr 2019 21:59:00 +0000 http://faculty.washington.edu/leeay/wordpress/?p=178 Continue reading "Generating retinal flow maps from structural optical coherence tomography with artificial intelligence"

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Fully automated, deep learning segmentation of oxygen-induced retinopathy images https://comp.ophthalmology.uw.edu/2017/12/21/fully-automated-deep-learning-segmentation-of-oxygen-induced-retinopathy-images-2/ Thu, 21 Dec 2017 23:14:00 +0000 http://faculty.washington.edu/leeay/wordpress/?p=619 Continue reading "Fully automated, deep learning segmentation of oxygen-induced retinopathy images"

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