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A multimodal deep learning system to distinguish late stages of AMD and to compare expert vs. AI ocu...

A multimodal deep learning system to distinguish late stages of AMD and to compare expert vs. AI ocu...

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_651cc9a0a69d429983ce065ff9784e8a

A multimodal deep learning system to distinguish late stages of AMD and to compare expert vs. AI ocular biomarkers

About this item

Full title

A multimodal deep learning system to distinguish late stages of AMD and to compare expert vs. AI ocular biomarkers

Publisher

London: Nature Publishing Group UK

Journal title

Scientific reports, 2022-02, Vol.12 (1), p.2585-2585, Article 2585

Language

English

Formats

Publication information

Publisher

London: Nature Publishing Group UK

More information

Scope and Contents

Contents

Within the next 1.5 decades, 1 in 7 U.S. adults is anticipated to suffer from age-related macular degeneration (AMD), a degenerative retinal disease which leads to blindness if untreated. Optical coherence tomography angiography (OCTA) has become a prime technique for AMD diagnosis, specifically for late-stage neovascular (NV) AMD. Such technologie...

Alternative Titles

Full title

A multimodal deep learning system to distinguish late stages of AMD and to compare expert vs. AI ocular biomarkers

Identifiers

Primary Identifiers

Record Identifier

TN_cdi_doaj_primary_oai_doaj_org_article_651cc9a0a69d429983ce065ff9784e8a

Permalink

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_651cc9a0a69d429983ce065ff9784e8a

Other Identifiers

ISSN

2045-2322

E-ISSN

2045-2322

DOI

10.1038/s41598-022-06273-w

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