(Q33224000)

24 July 2017

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

1 reference

independent component analysis

24 July 2017

unsupervised learning

1 reference

based on heuristic

inferred from title

1 reference

based on heuristic

inferred from title

author

Terrence J. Sejnowski

11

Terrence Sejnowski

0 references

Catherine Boden

Catherine Boden

7

0 references

Christopher Bowd

Christopher Bowd

8

0 references

Robert N Weinreb

13

Robert N Weinreb

1 reference

24 July 2017

10

Linda Zangwill

1 reference

24 July 2017

2

Pamela A Sample

1 reference

24 July 2017

1

Michael H Goldbaum

1 reference

24 July 2017

9

Rupert Bourne

1 reference

24 July 2017

Zuohua Zhang

3

1 reference

24 July 2017

Kwokleung Chan

4

1 reference

24 July 2017

Jiucang Hao

5

1 reference

24 July 2017

Te-Won Lee

6

1 reference

24 July 2017

David Spinak

12

1 reference

24 July 2017

language of work or name

English

0 references

publication date

1 October 2005

1 reference

Investigative Ophthalmology Visual Science

24 July 2017

1 reference

24 July 2017

46

1 reference

24 July 2017

3676-3683

1 reference

24 July 2017

10

1 reference

Variational Learning of Clusters of Undercomplete Nonsymmetric Independent Components

24 July 2017

1 reference

https://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pmc&linkname=pmc_refs_pubmed&retmode=json&id=1866286

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

14 July 2018

1 reference

https://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pmc&linkname=pmc_refs_pubmed&retmode=json&id=1866286

Using unsupervised learning with variational bayesian mixture of factor analysis to identify patterns of glaucomatous visual field defects

14 July 2018

1 reference

https://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pmc&linkname=pmc_refs_pubmed&retmode=json&id=1866286

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

14 July 2018

1 reference

https://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pmc&linkname=pmc_refs_pubmed&retmode=json&id=1866286

Spatial classification of glaucomatous visual field loss

14 July 2018

1 reference

https://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pmc&linkname=pmc_refs_pubmed&retmode=json&id=1866286

Using machine learning classifiers to identify glaucomatous change earlier in standard visual fields.

14 July 2018

1 reference

https://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pmc&linkname=pmc_refs_pubmed&retmode=json&id=1866286

Comparing machine learning classifiers for diagnosing glaucoma from standard automated perimetry.

31 October 2018

1 reference

https://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pmc&linkname=pmc_refs_pubmed&retmode=json&id=1866286

Neural networks to identify glaucoma with structural and functional measurements.

31 October 2018

1 reference

https://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pmc&linkname=pmc_refs_pubmed&retmode=json&id=1866286

Interpretation of automated perimetry for glaucoma by neural network

31 October 2018

1 reference

https://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pmc&linkname=pmc_refs_pubmed&retmode=json&id=1866286

Assessing the utility of reliability indices for automated visual fields. Testing ocular hypertensives

31 October 2018

1 reference

PubMed

https://pubmed.ncbi.nlm.nih.gov/16186349

inferred from PubMed ID database lookup

12 December 2020

based on heuristic

Identifiers

DOI

10.1167/IOVS.04-1167

1 reference

24 July 2017

1 reference

24 July 2017

1 reference