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Michael H Goldbaum

Showing results (31-40 of 65) with videos related to

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Investigative Ophthalmology & Visual Science|March 26, 2005
Relevance vector machine and support vector machine classifier analysis of scanning laser polarimetry retinal nerve fiber layer measurementsChristopher Bowd, Felipe A Medeiros, Zuohua Zhang, et al.
Investigative Ophthalmology & Visual Science|March 20, 2012
Predicting glaucomatous progression in glaucoma suspect eyes using relevance vector machine classifiers for combined structural and functional measurementsChristopher Bowd, Intae Lee, Michael H Goldbaum, et al.
Scientific Reports|November 14, 2018
Performance of Deep Learning Architectures and Transfer Learning for Detecting Glaucomatous Optic Neuropathy in Fundus PhotographsMark Christopher, Akram Belghith, Christopher Bowd, et al.
Ophthalmology|November 14, 2019
Deep Learning Approaches Predict Glaucomatous Visual Field Damage from OCT Optic Nerve Head En Face Images and Retinal Nerve Fiber Layer Thickness MapsMark Christopher, Christopher Bowd, Akram Belghith, et al.
Translational Vision Science & Technology|October 14, 2025
Assessing the Clinical Utility of Multimodal Large Language Models in the Diagnosis and Management of Pigmented Choroidal LesionsNehal Nailesh Mehta, Evan Walker, Elena Flester, et al.
American Journal of Ophthalmology|March 31, 2020
Gradient-Boosting Classifiers Combining Vessel Density and Tissue Thickness Measurements for Classifying Early to Moderate GlaucomaChristopher Bowd, Akram Belghith, James A Proudfoot, et al.
Ophthalmology. Retina|May 19, 2022
Retinal Ischemic Perivascular Lesions, a Biomarker of Cardiovascular DiseaseSamantha Madala, Fatemeh Adabifirouzjaei, Leonardo Lando, et al.
Investigative Ophthalmology & Visual Science|March 11, 2008
Bayesian machine learning classifiers for combining structural and functional measurements to classify healthy and glaucomatous eyesChristopher Bowd, Jiucang Hao, Ivan M Tavares, et al.
American Journal of Ophthalmology|November 15, 2021
Deep Learning Image Analysis of Optical Coherence Tomography Angiography Measured Vessel Density Improves Classification of Healthy and Glaucoma EyesChristopher Bowd, Akram Belghith, Linda M Zangwill, et al.
Investigative Ophthalmology & Visual Science|July 31, 2002
Using machine learning classifiers to identify glaucomatous change earlier in standard visual fieldsPamela A Sample, Michael H Goldbaum, Kwokleung Chan, et al.
Pageof 7

Showing results (31-40 of 65) with videos related to

Sort By:
Pageof 7
Investigative Ophthalmology & Visual Science|March 26, 2005
Relevance vector machine and support vector machine classifier analysis of scanning laser polarimetry retinal nerve fiber layer measurementsChristopher Bowd, Felipe A Medeiros, Zuohua Zhang, et al.
Investigative Ophthalmology & Visual Science|March 20, 2012
Predicting glaucomatous progression in glaucoma suspect eyes using relevance vector machine classifiers for combined structural and functional measurementsChristopher Bowd, Intae Lee, Michael H Goldbaum, et al.
Scientific Reports|November 14, 2018
Performance of Deep Learning Architectures and Transfer Learning for Detecting Glaucomatous Optic Neuropathy in Fundus PhotographsMark Christopher, Akram Belghith, Christopher Bowd, et al.
Ophthalmology|November 14, 2019
Deep Learning Approaches Predict Glaucomatous Visual Field Damage from OCT Optic Nerve Head En Face Images and Retinal Nerve Fiber Layer Thickness MapsMark Christopher, Christopher Bowd, Akram Belghith, et al.
Translational Vision Science & Technology|October 14, 2025
Assessing the Clinical Utility of Multimodal Large Language Models in the Diagnosis and Management of Pigmented Choroidal LesionsNehal Nailesh Mehta, Evan Walker, Elena Flester, et al.
American Journal of Ophthalmology|March 31, 2020
Gradient-Boosting Classifiers Combining Vessel Density and Tissue Thickness Measurements for Classifying Early to Moderate GlaucomaChristopher Bowd, Akram Belghith, James A Proudfoot, et al.
Ophthalmology. Retina|May 19, 2022
Retinal Ischemic Perivascular Lesions, a Biomarker of Cardiovascular DiseaseSamantha Madala, Fatemeh Adabifirouzjaei, Leonardo Lando, et al.
Investigative Ophthalmology & Visual Science|March 11, 2008
Bayesian machine learning classifiers for combining structural and functional measurements to classify healthy and glaucomatous eyesChristopher Bowd, Jiucang Hao, Ivan M Tavares, et al.
American Journal of Ophthalmology|November 15, 2021
Deep Learning Image Analysis of Optical Coherence Tomography Angiography Measured Vessel Density Improves Classification of Healthy and Glaucoma EyesChristopher Bowd, Akram Belghith, Linda M Zangwill, et al.
Investigative Ophthalmology & Visual Science|July 31, 2002
Using machine learning classifiers to identify glaucomatous change earlier in standard visual fieldsPamela A Sample, Michael H Goldbaum, Kwokleung Chan, et al.
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