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Medeiros FA 46
Showing records 1 to 25 | Display all abstracts from Medeiros FA76300 The Association Between Macula and ONH Optical Coherence Tomography Angiography (OCT-A) Vessel Densities in Glaucoma, Glaucoma Suspect, and Healthy Eyes
Manalastas PIC
Journal of Glaucoma 2018; 27: 227-232
77238 Retinal Nerve Fiber Layer Features Identified by Unsupervised Machine Learning on Optical Coherence Tomography Scans Predict Glaucoma Progression
Christopher M
Investigative Ophthalmology and Visual Science 2018; 59: 2748-2756
76259 Recent developments in visual field testing for glaucoma
Wu Z
Current Opinions in Ophthalmology 2018; 29: 141-146
76746 Impact of Different Visual Field Testing Paradigms on Sample Size Requirements for Glaucoma Clinical Trials
Wu Z
Scientific reports 2018; 8: 4889
77303 Development of a Visual Field Simulation Model of Longitudinal Point-Wise Sensitivity Changes From a Clinical Glaucoma Cohort
Wu Z
Translational vision science & technology 2018; 7: 22
77080 Automated Beta Zone Parapapillary Area Measurement to Differentiate Between Healthy and Glaucoma Eyes
Manalastas PIC
American Journal of Ophthalmology 2018; 191: 140-148
76870 Event-based analysis of visual field change can miss fast glaucoma progression detected by a combined structure and function index
Zhang C
Graefe's Archive for Clinical and Experimental Ophthalmology 2018; 256: 1227-1234
76514 Detection of Glaucoma Progression in Individuals of African Descent Compared With Those of European Descent
Gracitelli CPB
JAMA ophthalmology 2018; 136: 329-335
77080 Automated Beta Zone Parapapillary Area Measurement to Differentiate Between Healthy and Glaucoma Eyes
Belghith A
American Journal of Ophthalmology 2018; 191: 140-148
76870 Event-based analysis of visual field change can miss fast glaucoma progression detected by a combined structure and function index
Tatham AJ
Graefe's Archive for Clinical and Experimental Ophthalmology 2018; 256: 1227-1234
77238 Retinal Nerve Fiber Layer Features Identified by Unsupervised Machine Learning on Optical Coherence Tomography Scans Predict Glaucoma Progression
Belghith A
Investigative Ophthalmology and Visual Science 2018; 59: 2748-2756
76514 Detection of Glaucoma Progression in Individuals of African Descent Compared With Those of European Descent
Zangwill LM
JAMA ophthalmology 2018; 136: 329-335
76259 Recent developments in visual field testing for glaucoma
Medeiros FA
Current Opinions in Ophthalmology 2018; 29: 141-146
76300 The Association Between Macula and ONH Optical Coherence Tomography Angiography (OCT-A) Vessel Densities in Glaucoma, Glaucoma Suspect, and Healthy Eyes
Zangwill LM
Journal of Glaucoma 2018; 27: 227-232
76746 Impact of Different Visual Field Testing Paradigms on Sample Size Requirements for Glaucoma Clinical Trials
Medeiros FA
Scientific reports 2018; 8: 4889
77303 Development of a Visual Field Simulation Model of Longitudinal Point-Wise Sensitivity Changes From a Clinical Glaucoma Cohort
Medeiros FA
Translational vision science & technology 2018; 7: 22
76870 Event-based analysis of visual field change can miss fast glaucoma progression detected by a combined structure and function index
Daga FB
Graefe's Archive for Clinical and Experimental Ophthalmology 2018; 256: 1227-1234
77080 Automated Beta Zone Parapapillary Area Measurement to Differentiate Between Healthy and Glaucoma Eyes
Weinreb RN
American Journal of Ophthalmology 2018; 191: 140-148
76514 Detection of Glaucoma Progression in Individuals of African Descent Compared With Those of European Descent
Diniz-Filho A
JAMA ophthalmology 2018; 136: 329-335
76300 The Association Between Macula and ONH Optical Coherence Tomography Angiography (OCT-A) Vessel Densities in Glaucoma, Glaucoma Suspect, and Healthy Eyes
Daga FB
Journal of Glaucoma 2018; 27: 227-232
77238 Retinal Nerve Fiber Layer Features Identified by Unsupervised Machine Learning on Optical Coherence Tomography Scans Predict Glaucoma Progression
Weinreb RN
Investigative Ophthalmology and Visual Science 2018; 59: 2748-2756
77080 Automated Beta Zone Parapapillary Area Measurement to Differentiate Between Healthy and Glaucoma Eyes
Jonas JB
American Journal of Ophthalmology 2018; 191: 140-148
77238 Retinal Nerve Fiber Layer Features Identified by Unsupervised Machine Learning on Optical Coherence Tomography Scans Predict Glaucoma Progression
Bowd C
Investigative Ophthalmology and Visual Science 2018; 59: 2748-2756
76300 The Association Between Macula and ONH Optical Coherence Tomography Angiography (OCT-A) Vessel Densities in Glaucoma, Glaucoma Suspect, and Healthy Eyes
Christopher MA
Journal of Glaucoma 2018; 27: 227-232
76514 Detection of Glaucoma Progression in Individuals of African Descent Compared With Those of European Descent
Abe RY
JAMA ophthalmology 2018; 136: 329-335
