The DOI matches its Crossref record; 61 of the 61 references it cites were found in a registry or an index.
Algorithms for the Automated Detection of Diabetic Retinopathy Using Digital Fundus Images: A Review
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Role of Insulin Resistance in Human Disease
Reaven, G. M. (1988) · Diabetes · doi:10.2337/diab.37.12.1595 · Cited by 12,154
Brenner, B. M., Cooper, M. E., de Zeeuw, D., Keane, W. F., Mitch, W. E., Parving, H.-H., Remuzzi, G., Snapinn, S. M., Zhang, Z., & Shahinfar, S. (2001) · New England Journal of Medicine · doi:10.1056/nejmoa011161 · Cited by 7,493
(2007) · Developments in Ophthalmology · doi:10.1159/isbn.978-3-318-01439-6 · Cited by 5,583
Banting lecture 1988. Role of insulin resistance in human disease
Reaven, G. M. (1988) · Diabetes · doi:10.2337/diabetes.37.12.1595 · Cited by 3,811
Grundy, S. M., Benjamin, I. J., Burke, G. L., Chait, A., Eckel, R. H., Howard, B. V., Mitch, W., Smith, S. C., & Sowers, J. R. (1999) · Circulation · doi:10.1161/01.cir.100.10.1134 · Cited by 2,698
Locating blood vessels in retinal images by piecewise threshold probing of a matched filter response
Hoover, A. D., Kouznetsova, V., & Goldbaum, M. (2000) · IEEE Transactions on Medical Imaging · doi:10.1109/42.845178 · Cited by 2,582
Texture analysis using gray level run lengths
Galloway, M. M. (1975) · Computer Graphics and Image Processing · doi:10.1016/s0146-664x(75)80008-6 · Cited by 2,141
(1991) · Ophthalmology · doi:10.1016/s0161-6420(13)38012-9 · Cited by 2,048
2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition
(2001) · Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition CVPR 2001 CVPR-01 · doi:10.1109/cvpr.2001.990916 · Cited by 1,876
Tüceryan, M., & Jain, A. K. (1993) · Cited by 1,837
Cited by
Transfer learning techniques for medical image analysis: A review
Kora, P., Ooi, C. P., Faust, O., Raghavendra, U., Gudigar, A., Chan, W. Y., Meenakshi, K., Swaraja, K., Plawiak, P., & Rajendra Acharya, U. (2022) · Biocybernetics and Biomedical Engineering · doi:10.1016/j.bbe.2021.11.004 · Cited by 367
Self-citationComparative approaches for classification of diabetes mellitus data: Machine learning paradigm
Maniruzzaman, M., Kumar, N., Menhazul Abedin, M., Shaykhul Islam, M., Suri, H. S., El-Baz, A. S., & Suri, J. S. (2017) · Computer Methods and Programs in Biomedicine · doi:10.1016/j.cmpb.2017.09.004 · Cited by 270
Self-citationEvaluation of Artificial Intelligence–Based Grading of Diabetic Retinopathy in Primary Care
Kanagasingam, Y., Xiao, D., Vignarajan, J., Preetham, A., Tay-Kearney, M.-L., & Mehrotra, A. (2018) · JAMA Network Open · doi:10.1001/jamanetworkopen.2018.2665 · Cited by 185
Li, F., Liu, Z., Chen, H., Jiang, M., Zhang, X., & Wu, Z. (2019) · Translational Vision Science & Technology · doi:10.1167/tvst.8.6.4 · Cited by 144
Contemporary retinal imaging techniques in diabetic retinopathy: a review
Cole, E. D., Novais, E. A., Louzada, R. N., & Waheed, N. K. (2016) · Clinical & Experimental Ophthalmology · doi:10.1111/ceo.12711 · Cited by 91
Metadata
- Authors
- Faust, O., Acharya U., R., Ng, E. Y. K., Ng, K.-H., & Suri, J. S.
- Venue
- Journal of Medical Systems
- Published
- 2010-04-06
- Volume
- 36
- Issue
- 1
- Pages
- 145-157
- ISSN
- 0148-5598 (ISSN-L)
- 1573-689X
- OpenAlex
- W1976647582
- Cited by
- 303
- References
- 61
- FWCI
- 6.75
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Algorithms for the Automated Detection of Diabetic Retinopathy Using Digital Fundus Images: A Review. https://app.cochat.ai/papers/10.1007/s10916-010-9454-7
- The paper
- Faust, O., Acharya U., R., Ng, E. Y. K., Ng, K.-H., & Suri, J. S. (2012). Algorithms for the Automated Detection of Diabetic Retinopathy Using Digital Fundus Images: A Review. Journal of Medical Systems. https://doi.org/10.1007/s10916-010-9454-7
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
