Predicting optical coherence tomography-derived diabetic macular edema grades from fundus photograph...
Predicting optical coherence tomography-derived diabetic macular edema grades from fundus photographs using deep learning
About this item
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Author / Creator
Varadarajan, Avinash V. , Bavishi, Pinal , Ruamviboonsuk, Paisan , Chotcomwongse, Peranut , Venugopalan, Subhashini , Narayanaswamy, Arunachalam , Cuadros, Jorge , Kanai, Kuniyoshi , Bresnick, George , Tadarati, Mongkol , Silpa-archa, Sukhum , Limwattanayingyong, Jirawut , Nganthavee, Variya , Ledsam, Joseph R. , Keane, Pearse A. , Corrado, Greg S. , Peng, Lily and Webster, Dale R.
Publisher
London: Nature Publishing Group UK
Journal title
Language
English
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Publication information
Publisher
London: Nature Publishing Group UK
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Scope and Contents
Contents
Center-involved diabetic macular edema (ci-DME) is a major cause of vision loss. Although the gold standard for diagnosis involves 3D imaging, 2D imaging by fundus photography is usually used in screening settings, resulting in high false-positive and false-negative calls. To address this, we train a deep learning model to predict ci-DME from fundu...
Alternative Titles
Full title
Predicting optical coherence tomography-derived diabetic macular edema grades from fundus photographs using deep learning
Authors, Artists and Contributors
Author / Creator
Bavishi, Pinal
Ruamviboonsuk, Paisan
Chotcomwongse, Peranut
Venugopalan, Subhashini
Narayanaswamy, Arunachalam
Cuadros, Jorge
Kanai, Kuniyoshi
Bresnick, George
Tadarati, Mongkol
Silpa-archa, Sukhum
Limwattanayingyong, Jirawut
Nganthavee, Variya
Ledsam, Joseph R.
Keane, Pearse A.
Corrado, Greg S.
Peng, Lily
Webster, Dale R.
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Primary Identifiers
Record Identifier
TN_cdi_doaj_primary_oai_doaj_org_article_00d3202651b84a36837950c21fab3fb0
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_00d3202651b84a36837950c21fab3fb0
Other Identifiers
ISSN
2041-1723
E-ISSN
2041-1723
DOI
10.1038/s41467-019-13922-8
