Deep Learning vs. Human Graders for Classifying Severity Levels of Diabetic Retinopathy in a Real-World Nationwide Screening Program Article Swipe
Paisan Raumviboonsuk
,
Jonathan Krause
,
Peranut Chotcomwongse
,
Rory Sayres
,
Rajiv Raman
,
Kasumi Widner
,
Bilson Campana
,
Sonia Phene
,
Kornwipa Hemarat
,
Mongkol Tadarati
,
Sukhum Silpa‐archa
,
Jirawut Limwattanayingyong
,
Chetan Rao
,
Oscar Kuruvilla
,
Jesse J. Jung
,
Jeffrey J. Tan
,
Surapong Orprayoon
,
Chawawat Kangwanwongpaisan
,
Ramase Sukulmalpaiboon
,
Chainarong Luengchaichawang
,
Jitumporn Fuangkaew
,
Pipat Kongsap
,
Lamyong Chualinpha
,
Sarawuth Saree
,
Srirat Kawinpanitan
,
Korntip Mitvongsa
,
Siriporn Lawanasakol
,
Chaiyasit Thepchatri
,
Lalita Wongpichedchai
,
Gregory S. Corrado
,
Lily Peng
,
Dale R. Webster
·
YOU?
·
· 2018
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.1810.08290
YOU?
·
· 2018
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.1810.08290
Deep learning algorithms have been used to detect diabetic retinopathy (DR) with specialist-level accuracy. This study aims to validate one such algorithm on a large-scale clinical population, and compare the algorithm performance with that of human graders. 25,326 gradable retinal images of patients with diabetes from the community-based, nation-wide screening program of DR in Thailand were analyzed for DR severity and referable diabetic macular edema (DME). Grades adjudicated by a panel of international retinal specialists served as the reference standard. Across different severity levels of DR for determining referable disease, deep learning significantly reduced the false negative rate (by 23%) at the cost of slightly higher false positive rates (2%). Deep learning algorithms may serve as a valuable tool for DR screening.
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Metadata
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/1810.08290
- https://arxiv.org/pdf/1810.08290
- OA Status
- green
- Cited By
- 11
- References
- 11
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W2896596918
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W2896596918Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.48550/arxiv.1810.08290Digital Object Identifier
- Title
-
Deep Learning vs. Human Graders for Classifying Severity Levels of Diabetic Retinopathy in a Real-World Nationwide Screening ProgramWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2018Year of publication
- Publication date
-
2018-10-18Full publication date if available
- Authors
-
Paisan Raumviboonsuk, Jonathan Krause, Peranut Chotcomwongse, Rory Sayres, Rajiv Raman, Kasumi Widner, Bilson Campana, Sonia Phene, Kornwipa Hemarat, Mongkol Tadarati, Sukhum Silpa‐archa, Jirawut Limwattanayingyong, Chetan Rao, Oscar Kuruvilla, Jesse J. Jung, Jeffrey J. Tan, Surapong Orprayoon, Chawawat Kangwanwongpaisan, Ramase Sukulmalpaiboon, Chainarong Luengchaichawang, Jitumporn Fuangkaew, Pipat Kongsap, Lamyong Chualinpha, Sarawuth Saree, Srirat Kawinpanitan, Korntip Mitvongsa, Siriporn Lawanasakol, Chaiyasit Thepchatri, Lalita Wongpichedchai, Gregory S. Corrado, Lily Peng, Dale R. WebsterList of authors in order
- Landing page
-
https://arxiv.org/abs/1810.08290Publisher landing page
- PDF URL
-
https://arxiv.org/pdf/1810.08290Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
-
https://arxiv.org/pdf/1810.08290Direct OA link when available
- Concepts
-
Diabetic retinopathy, Medicine, Deep learning, Optometry, Diabetes mellitus, False positive rate, Diabetic macular edema, Artificial intelligence, Retinopathy, Population, Machine learning, Ophthalmology, Computer science, Environmental health, EndocrinologyTop concepts (fields/topics) attached by OpenAlex
- Cited by
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11Total citation count in OpenAlex
- Citations by year (recent)
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2024: 1, 2021: 3, 2020: 3, 2019: 4Per-year citation counts (last 5 years)
- References (count)
-
11Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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