List of works - Michael H Goldbaum

Assessing visual field clustering schemes using machine learning classifiers in standard perimetry

scientific article published on December 2007

Bayesian machine learning classifiers for combining structural and functional measurements to classify healthy and glaucomatous eyes

scientific article

Combining functional and structural tests improves the diagnostic accuracy of relevance vector machine classifiers

scientific article

Comparing neural networks and linear discriminant functions for glaucoma detection using confocal scanning laser ophthalmoscopy of the optic disc

scientific article

Confocal scanning laser ophthalmoscopy classifiers and stereophotograph evaluation for prediction of visual field abnormalities in glaucoma-suspect eyes

scientific article published in July 2004

Deep Learning Approaches Predict Glaucomatous Visual Field Damage from OCT Optic Nerve Head En Face Images and Retinal Nerve Fiber Layer Thickness Maps

scientific article published on 30 September 2019

Detecting glaucomatous change in visual fields: Analysis with an optimization framework

scientific article

Glaucoma progression detection using structural retinal nerve fiber layer measurements and functional visual field points

scientific article

Glaucomatous patterns in Frequency Doubling Technology (FDT) perimetry data identified by unsupervised machine learning classifiers

scientific article

Gradient Boosting Classifiers Combining Vessel Density and Tissue Thickness Measurements for Classifying Early to Moderate Glaucoma

scientific article published on 25 March 2020

Heidelberg retina tomograph measurements of the optic disc and parapapillary retina for detecting glaucoma analyzed by machine learning classifiers

scientific article

Learning from data: recognizing glaucomatous defect patterns and detecting progression from visual field measurements

scientific article

Performance of Deep Learning Architectures and Transfer Learning for Detecting Glaucomatous Optic Neuropathy in Fundus Photographs

scientific article published in Scientific Reports

Predicting glaucomatous progression in glaucoma suspect eyes using relevance vector machine classifiers for combined structural and functional measurements

scientific article

Progression of patterns (POP): a machine classifier algorithm to identify glaucoma progression in visual fields

scientific article

Relevance vector machine and support vector machine classifier analysis of scanning laser polarimetry retinal nerve fiber layer measurements

scientific article published in April 2005

Retinal Nerve Fiber Layer Features Identified by Unsupervised Machine Learning on Optical Coherence Tomography Scans Predict Glaucoma Progression.

scientific article published in June 2018

Unsupervised Gaussian Mixture-Model With Expectation Maximization for Detecting Glaucomatous Progression in Standard Automated Perimetry Visual Fields

scientific article published on 3 May 2016

Unsupervised machine learning with independent component analysis to identify areas of progression in glaucomatous visual fields

scientific article published on October 2005

Using unsupervised learning with independent component analysis to identify patterns of glaucomatous visual field defects

scientific article published in October 2005

List of works by Michael H Goldbaum

Assessing visual field clustering schemes using machine learning classifiers in standard perimetry

Bayesian machine learning classifiers for combining structural and functional measurements to classify healthy and glaucomatous eyes

Combining functional and structural tests improves the diagnostic accuracy of relevance vector machine classifiers

Comparing neural networks and linear discriminant functions for glaucoma detection using confocal scanning laser ophthalmoscopy of the optic disc

Confocal scanning laser ophthalmoscopy classifiers and stereophotograph evaluation for prediction of visual field abnormalities in glaucoma-suspect eyes

Deep Learning Approaches Predict Glaucomatous Visual Field Damage from OCT Optic Nerve Head En Face Images and Retinal Nerve Fiber Layer Thickness Maps

Detecting glaucomatous change in visual fields: Analysis with an optimization framework

Glaucoma progression detection using structural retinal nerve fiber layer measurements and functional visual field points

Glaucomatous patterns in Frequency Doubling Technology (FDT) perimetry data identified by unsupervised machine learning classifiers

Gradient Boosting Classifiers Combining Vessel Density and Tissue Thickness Measurements for Classifying Early to Moderate Glaucoma

Heidelberg retina tomograph measurements of the optic disc and parapapillary retina for detecting glaucoma analyzed by machine learning classifiers

Learning from data: recognizing glaucomatous defect patterns and detecting progression from visual field measurements

Performance of Deep Learning Architectures and Transfer Learning for Detecting Glaucomatous Optic Neuropathy in Fundus Photographs

Predicting glaucomatous progression in glaucoma suspect eyes using relevance vector machine classifiers for combined structural and functional measurements

Progression of patterns (POP): a machine classifier algorithm to identify glaucoma progression in visual fields

Relevance vector machine and support vector machine classifier analysis of scanning laser polarimetry retinal nerve fiber layer measurements

Retinal Nerve Fiber Layer Features Identified by Unsupervised Machine Learning on Optical Coherence Tomography Scans Predict Glaucoma Progression.

Unsupervised Gaussian Mixture-Model With Expectation Maximization for Detecting Glaucomatous Progression in Standard Automated Perimetry Visual Fields

Unsupervised machine learning with independent component analysis to identify areas of progression in glaucomatous visual fields

Using unsupervised learning with independent component analysis to identify patterns of glaucomatous visual field defects