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

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

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

http://www.wikidata.org/entity/Q34199522

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Glaucomatous patterns in Frequency Doubling Technology (FDT) perimetry data identified by unsupervised machine learning classifiers Detecting glaucomatous change in visual fields: Analysis with an optimization framework Unsupervised Gaussian Mixture-Model With Expectation Maximization for Detecting Glaucomatous Progression in Standard Automated Perimetry Visual Fields.Predicting progression in glaucoma suspects with longitudinal estimates of retinal ganglion cell counts.Development and validation of an improved neurological hemifield test to identify chiasmal and postchiasmal lesions by automated perimetry.Machine Learning Techniques in Clinical Vision Sciences.

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P2860

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

http://www.wikidata.org/entity/Q34199522

description

2012 nî lūn-bûn

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2012 թուականի Ապրիլին հրատարակուած գիտական յօդուած

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2012 թվականի ապրիլին հրատարակված գիտական հոդված

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2012年の論文

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2012年論文

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2012年論文

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2012年論文

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2012年論文

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2012年論文

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2012年论文

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name

Predicting glaucomatous progre ...... al and functional measurements

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Predicting glaucomatous progre ...... al and functional measurements

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Predicting glaucomatous progre ...... al and functional measurements

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Predicting glaucomatous progre ...... al and functional measurements

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Predicting glaucomatous progre ...... al and functional measurements

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Predicting glaucomatous progre ...... al and functional measurements

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Predicting glaucomatous progre ...... al and functional measurements

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Predicting glaucomatous progre ...... al and functional measurements

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Predicting glaucomatous progre ...... al and functional measurements

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Investigative Ophthalmology & Visual Science

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Predicting glaucomatous progre ...... al and functional measurements

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P2093

Christopher A Girkin

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Christopher Bowd

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Felipe A Medeiros

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Intae Lee

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Jeffrey M Liebmann

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Madhusudhanan Balasubramanian

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Michael H Goldbaum

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P2860

The meaning and use of the area under a receiver operating characteristic (ROC) curve

A Unified Approach to Nonparametric Comparison of Receiver Operating Characteristic Curves for Longitudinal and Clustered Data.

Early Manifest Glaucoma Trial: design and baseline data.

A non-parametric method for the comparison of partial areas under ROC curves and its application to large health care data sets.

Effects of input data on the performance of a neural network in distinguishing normal and glaucomatous visual fields.

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

Retinal nerve fiber layer thickness measurements with scanning laser polarimetry predict glaucomatous visual field loss.

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

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

Baseline topographic optic disc measurements are associated with the development of primary open-angle glaucoma: the Confocal Scanning Laser Ophthalmoscopy Ancillary Study to the Ocular Hypertension Treatment Study.

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2382-2389

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10.1167/IOVS.11-7951

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4

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Robert N Weinreb

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2012-04-30T00:00:00Z

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221715987

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22427577

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Relevance vector machine

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3760232

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