Paper · 35352000

Detection of signs of disease in external photographs of the eyes via deep learning.

Babenko B and 12 others. Nat Biomed Eng, 2022. Cited by 49 papers, by iCite.

11 sourcespapers-2026-11-12-0.1.0

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ConductScience Library. Detection of signs of disease in external photographs of the eyes via deep learning. Papers, record 35352000. Release papers-2026-11-12-0.1.0, 12 Nov 2026. https://conductscience.org/library/papers/35352000

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Paper

PubMed's record of the paper, with iCite's citation figures. No abstract is shown.

Title: Detection of signs of disease in external photographs of the eyes via deep learning.; PubMed
Journal: Nat Biomed Eng; PubMed
Year: 2022; PubMed
Publication types: Journal Article, Research Support, Non-U.S. Gov't; PubMed
PubMed: https://pubmed.ncbi.nlm.nih.gov/35352000/; PubMed
DOI: https://doi.org/10.1038/s41551-022-00867-5; PubMed
PMC: https://pmc.ncbi.nlm.nih.gov/articles/PMC8963675/; PubMed
The journal: https://conductscience.org/library/journal-index/101696896; PubMed
Citations, by iCite: 49; iCite
Relative citation ratio, by iCite: 4.95; iCite
Revised in PubMed: 2025-09-04; PubMed

Authors13

The authors in the order PubMed's record lists them, with the ORCID iDs it states.

Order	Author	Forename	ORCID iD
1	Babenko B	Boris
2	Mitani A	Akinori	https://orcid.org/0000-0001-8088-6021
3	Traynis I	Ilana
4	Kitade N	Naho
5	Singh P	Preeti
6	Maa AY	April Y
7	Cuadros J	Jorge
8	Corrado GS	Greg S
9	Peng L	Lily
10	Webster DR	Dale R	https://orcid.org/0000-0002-3023-8824

1 to 10 of 13Source PubMed

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Topics6

NLM's MeSH indexing of the paper, its major topics first.

MeSH term	Major
Deep Learning	Major topic
Diabetic Retinopathy	Major topic
Retinal Diseases	Major topic
Humans
Sensitivity and Specificity
Fundus Oculi

Source PubMed

Grants0

Each grant PubMed's record writes, matched to the NIH project NIH's grant and paper links name for this paper, and each of those links the record does not write.

None in this release.

Trials0

The trials whose ClinicalTrials.gov record lists the paper, and the trial numbers the paper's PubMed record names.

None in this release.

Comments and corrections1

PubMed's comments and corrections, NLM's own indexing: retractions first, then expressions of concern, errata and updates, and comments last.

Kind	PMID	Title	In Papers
Comment in	35,411,115	Eyeing severe diabetes upfront.	https://conductscience.org/library/papers/35411115

Source PubMed

References51

The papers the reference list in PubMed's record names, those in our copy of PubMed, in the list's order.

Order	PMID	Title	Journal	Year	In Papers	Source
1	31,015,713	Prediction of cardiovascular risk factors from retinal fundus photographs via deep learning.	Nat Biomed Eng	2018	https://conductscience.org/library/papers/31015713	PubMed
2	31,873,211	Detection of anaemia from retinal fundus images via deep learning.	Nat Biomed Eng	2020	https://conductscience.org/library/papers/31873211	PubMed
3	33,328,123	A deep learning algorithm to detect chronic kidney disease from retinal photographs in community-based populations.	Lancet Digit Health	2020	https://conductscience.org/library/papers/33328123	PubMed
4	33,328,047	Prediction of systemic biomarkers from retinal photographs: development and validation of deep-learning algorithms.	Lancet Digit Health	2020	https://conductscience.org/library/papers/33328047	PubMed
5	23,843,690	Subconjunctival hemorrhage: risk factors and potential indicators.	Clin Ophthalmol	2013	https://conductscience.org/library/papers/23843690	PubMed
6	6,759,259	Pupil size in insulin-dependent diabetes. Relationship to duration, metabolic control, and long-term manifestations.	Diabetes	1982	https://conductscience.org/library/papers/6759259	PubMed
7	709,128	Pupillary signs in diabetic autonomic neuropathy.	Br Med J	1978	https://conductscience.org/library/papers/709128	PubMed
8	29,090,043	Distribution of Different Sized Ocular Surface Vessels in Diabetics and Normal Individuals.	J Ophthalmic Vis Res	2017	https://conductscience.org/library/papers/29090043	PubMed
9	30,440,269	Detection of Diabetes by Macrovascular Tortuosity of Superior Bulbar Conjunctiva.	Annu Int Conf IEEE Eng Med Biol Soc	2018	https://conductscience.org/library/papers/30440269	PubMed
10	21,577,356	Pupillary responses to single and sinusoidal light stimuli in diabetic patients.	Neurol Int	2009	https://conductscience.org/library/papers/21577356	PubMed

1 to 10 of 51

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Cited by36

The papers in our copy of PubMed whose reference list names this one, newest first. iCite, which reads more sources, counts 49 citations.

PMID	Title	Journal	Year	In Papers	Source
42,668,860	Artificial intelligence-enhanced electrocardiography for the prediction of future type 2 diabetes mellitus: a model-development and multicentre validation study.	Eur Heart J Digit Health	2026	https://conductscience.org/library/papers/42668860	PubMed
42,417,850	Which features best differentiate Sjögren's-related from non-Sjögren's-related dry eye disease?	Graefes Arch Clin Exp Ophthalmol	2026	https://conductscience.org/library/papers/42417850	PubMed
42,382,959	Oculomics: advances and perspectives from traditional Chinese medicine to modern multimodal biomarkers.	Int J Ophthalmol	2026	https://conductscience.org/library/papers/42382959	PubMed
42,277,173	Swin-DRNet: A robust transformer framework for diabetic retinopathy screening under heterogeneous imaging conditions.	Sci Rep	2026	https://conductscience.org/library/papers/42277173	PubMed
42,061,843	Simulated Workflow Feasibility Evaluation of a Web-Based Periorbital Measurement Platform: Development and Usability Study.	JMIR Hum Factors	2026	https://conductscience.org/library/papers/42061843	PubMed
41,469,469	A deep-learning system for the assessment of coronary heart disease risk via scleral photographs.	Sci Rep	2025	https://conductscience.org/library/papers/41469469	PubMed
41,161,843	Investigating the capability of deep learning models to predict age and biological sex from anterior segment ophthalmic imaging: a multi-centre retrospective study.	BMJ Open	2025	https://conductscience.org/library/papers/41161843	PubMed
40,858,339	Effectiveness and satisfaction of fully self-service fundus disease screening among middle-aged individuals: a cross-sectional study.	BMJ Open Ophthalmol	2025	https://conductscience.org/library/papers/40858339	PubMed
40,653,573	Diagnosing pathologic myopia by identifying morphologic patterns using ultra widefield images with deep learning.	NPJ Digit Med	2025	https://conductscience.org/library/papers/40653573	PubMed
39,972,098	Ensemble fuzzy deep learning for brain tumor detection.	Sci Rep	2025	https://conductscience.org/library/papers/39972098	PubMed

1 to 10 of 36

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Genes0

The genes the Gene search release ties to the paper: Swiss-Prot's references first, then PubTator's text mining.

None in this release.

Drugs0

The drugs whose trials, in the Pipelines release, list the paper.

None in this release.

Data0

The data bank entries PubMed's record names. Trial numbers are under Trials.

None in this release.

Data dates

The date of each source this release read.

PubMed: 2026-11-06; PubMed
iCite: 2026-11-05; iCite
PMC's ID file: 2026-11-05; PMC's ID file
NIH RePORTER's grant and paper links: 2026-11-01; NIH RePORTER's grant and paper links
Trials: 2026-11-12
Gene search: 2026-11-11
Pipelines: 2026-09-18

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ChEMBL, through Open TargetsCC BY-SA 3.0
ClinicalTrials.govNo license stated
HGNCCC0
iCiteCC BY 4.0
NCBI GenePublic domain (US government)
NIH RePORTER's grant and paper linksPublic domain
Open TargetsCC0 1.0
PMC's ID filePublic domain (US government)
PubMedNLM's terms
PubTator 3Public domain
UniProtCC BY 4.0

Each source's terms

ChEMBL, through Open TargetsCC BY-SA 3.0, for the parts from ChEMBL. Read on 8 Nov 2026 at https://platform-docs.opentargets.org/licence
ClinicalTrials.govnone stated
HGNCCC0: https://www.genenames.org/about/license/
iCiteCC BY 4.0
NCBI GeneNone named for the file. NCBI says information created by or for the US government on its site is in the public domain, and asks that NLM be acknowledged: https://www.ncbi.nlm.nih.gov/home/about/policies/
NIH RePORTER's grant and paper linksPublic domain (NIH RePORTER)
Open TargetsCC0 1.0. Open Targets asks that users cite its latest paper: Buniello et al. 2025, Open Targets Platform: facilitating therapeutic hypotheses building in drug discovery, Nucleic Acids Research 53(D1):D1467, PMID 39657122. Read on 8 Nov 2026 at https://platform-docs.opentargets.org/licence
PMC's ID fileNone named for the file. NCBI says information created by or for the US government on its site is in the public domain, and asks that NLM be acknowledged: https://www.ncbi.nlm.nih.gov/home/about/policies/
PubMedNLM's terms
PubTator 3Public domain
UniProtCC BY 4.0. UniProt's licence file: "All databases and documents in the UniProt FTP directory may be copied and redistributed freely, without advance permission, provided that this copyright statement is reproduced with each copy." UniProt asks that users cite its latest paper: The UniProt Consortium, UniProt: the Universal Protein Knowledgebase in 2025, Nucleic Acids Research 53:D609-D617, https://doi.org/10.1093/nar/gkae1010. Read on 9 Nov 2026 at https://www.uniprot.org/help/license

ClinicalTrials.gov's data carry an international copyright outside the United States: https://clinicaltrials.gov/about-site/terms-conditions.

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