The DOI matches its Crossref record; 26 of the 27 references it cites were found in a registry or an index.
EyePACS: An Adaptable Telemedicine System for Diabetic Retinopathy Screening
Open accessAbstract
Background: Annual retinal screening of patients with diabetes is the standard clinical practice to prevent visual impairment and blindness from diabetic retinopathy. Telemedicine-based diabetic retinopathy screening (DRS) in primary care settings can effectively detect sight-threatening retinopathy and significantly increase compliance with annual retinal exams. EyePACS is a license-free Web-based DRS system designed to simplify the process of image capture, transmission, and review. The system provides a flexible platform for collaboration among clinicians about diabetic retinopathy. Methods: Primary clinic personnel (i.e., nursing, technical, or administrative staff) are trained and certified by the EyePACS program to acquire retinal images from standard digital retinal cameras. Relevant clinical data and eight high-resolution images per patient (two external and six retinal images) are encrypted and transmitted to a secure Internet server, using a standard computer and Web browser. Images are then interpreted by certified EyePACS reviewers or local eye care providers who are certified through the EyePACS Retinopathy Grading System. Reports indicating retinopathy level and referral recommendations are transmitted back to primary care providers through the EyePACS Web site or through interfaces between EyePACS and Health Level 7-compliant electronic medical records or chronic disease registries. Results: The pilot phase of the EyePACS DRS program in California (2005–2006) recorded 3562 encounters. Since 2006, EyePACS has been expanded to over 120 primary care sites throughout California and elsewhere recording over 34,000 DRSs. The overall rate of referral is 8.21% for sight-threatening retinopathy and 7.83% for other conditions (e.g., cataract and glaucoma). Conclusion: The use of license-free Web-based software, standard interfaces, and flexible protocols has allowed primary care providers to adopt retinopathy screening with minimal effort and resources.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“The development of an open-source system, EyePACS [55], supporting diabetic retinopathy as well as other ocular disorders on a variety of platforms, has encouraged widespread adoption of the telemedicine approach [56].”
From Recent directions in telemedicine: Review of trends in research and practice (2015) · cites this paper as [56]
Citations
Cites
Wilkinson, C. P., Ferris, F. L., Klein, R., Lee, P. P., Agardh, C., Davis, M., Dills, D. G., Kampik, A., Pararajasegaram, R., & Verdaguer, J. (2003) · Ophthalmology · doi:10.1016/s0161-6420(03)00475-5 · Cited by 3,786
* (1991) · Ophthalmology · doi:10.1016/s0161-6420(13)38012-9 · Cited by 2,086
Medicine 2.0: Social Networking, Collaboration, Participation, Apomediation, and Openness
Eysenbach, G. (2008) · Journal of Medical Internet Research · doi:10.2196/jmir.1030 · Cited by 1,143
Fong, D. S., Aiello, L. P., Gardner, T. W., King, G. L., Blankenship, G. W., Cavallerano, J. D., Ferris, F. L., & Klein, R. (2004) · Diabetes Care · doi:10.2337/diacare.27.2007.s84 · Cited by 1,138
Fundus Photographic Risk Factors for Progression of Diabetic Retinopathy
* (1991) · Ophthalmology · doi:10.1016/s0161-6420(13)38014-2 · Cited by 972
Lin, D. Y., Blumenkranz, M. S., Brothers, R. J., & Grosvenor, D. (2002) · American Journal of Ophthalmology · doi:10.1016/s0002-9394(02)01522-2 · Cited by 328
Bursell, S., Cavallerano, J. D., CAVALLERANO, A. A., Clermont, A. C., Birkmire‐Peters, D. P., Aiello, L. P., & Aiello, L. M. (2001) · Ophthalmology · doi:10.1016/s0161-6420(00)00604-7 · Cited by 247
Klein, R., Klein, R., Neider, M. W., Hubbard, L. D., Meuer, S. M., & Brothers, R. J. (1985) · Ophthalmology · doi:10.1016/s0161-6420(85)34003-4 · Cited by 227
Longitudinal rates of annual eye examinations of persons with diabetes and chronic eye diseases
Lee, P. P., Feldman, Z. W., Ostermann, J., Brown, D. S., & Sloan, F. A. (2003) · Ophthalmology · doi:10.1016/s0161-6420(03)00817-0 · Cited by 184
Bresnick, G. H., Mukamel, D. B., Dickinson, J. C., et al. (2000) · Ophthalmology · doi:10.1016/s0161-6420(99)00010-x · Cited by 162
Self-citationFactors associated with having eye examinations in persons with diabetes
Moss, S. E. (1995) · Archives of Family Medicine · doi:10.1001/archfami.4.6.529 · Cited by 144
Taylor, C. R., Merin, L. M., Salunga, A. M., Hepworth, J. T., Crutcher, T. D., O’Day, D. M., & Pilon, B. A. (2007) · Diabetes Care · doi:10.2337/dc06-1509 · Cited by 122
Barriers to compliance with screening guidelines for diabetic retinopathy
Mukamel, B. D., Bresnick, H. G., Wang, Q., & Dickey, F. C. (1999) · Ophthalmic Epidemiology · doi:10.1076/opep.6.1.61.1563 · Cited by 112
Rudnisky, C. J., TENNANT, M. T. S., Weis, E., Ting, A., Hinz, B. J., & Greve, M. D. J. (2007) · Ophthalmology · doi:10.1016/j.ophtha.2006.12.010 · Cited by 103
Wilson, C., Horton, M. B., Cavallerano, J. D., & Aiello, L. M. (2005) · Diabetes Care · doi:10.2337/diacare.28.2.318 · Cited by 100
Boucher, M. C., Gresset, J. A., Angioï-Duprez, K., et al. (2003) · Canadian Journal of Ophthalmology · doi:10.1016/s0008-4182(03)80109-6 · Cited by 97
CAVALLERANO, A. A., Cavallerano, J. D., Katalinic, P., Tolson, A. M., Aiello, L. P., & Aiello, L. M. (2003) · Retina · doi:10.1097/00006982-200304000-00013 · Cited by 95
Clinical evaluation of patients with diabetic retinopathy
FRANSEN, S. R., Leonard-Martin, T. C., Feuer, W. J., & Hildebrand, P. L. (2002) · Ophthalmology · doi:10.1016/s0161-6420(01)00990-3 · Cited by 93
Whited, J. D. (2006) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2006.8.102 · Cited by 60
Screening Guidelines for Diabetic Retinopathy
American College of Physicians, American Diabetes Association, & American Academy of Ophthalmology (1992) · Annals of Internal Medicine · doi:10.7326/0003-4819-116-8-683 · Cited by 56
Lawrence, M. G. (2004) · PubMed Central · Cited by 48
EyePACS: An Open Source Clinical Communication System For Eye Care
Cuadros, J. A., & Sim, I. (2004) · Studies in health technology and informatics · doi:10.3233/978-1-60750-949-3-207 · Cited by 35
Self-citationSchiffman, R. M., Jacobsen, G., Nussbaum, J. J., Desai, U. R., Carey, J. D., Glasser, D., Zimmer-Galler, I. E., Zeimer, R. C., & Goldberg, M. F. (2005) · Ophthalmic surgery, lasers & imaging retina · doi:10.3928/15428877-20050101-06 · Cited by 31
Research works printed but not linked: 2
- Lawrence MG, 2004, Trans Am Ophthalmol Soc., 102, 321
- Cuadros J, 2004, Stud Health Technol Inform., 107, 207
Cited by
Sorted by citations
Automated Identification of Diabetic Retinopathy Using Deep Learning
Gargeya, R., & Leng, T. (2017) · Ophthalmology · doi:10.1016/j.ophtha.2017.02.008 · Cited by 1,410
“We derived our predictive algorithm from a data set of 75 137 color fundus images obtained from the EyePACS public data set (EyePACS LLC, Berkeley, CA).(17) The images represented a heterogeneous cohort of patients with all stages of DR.”
MethodTransformers in medical imaging: A survey
Shamshad, F., Khan, S., Zamir, S. W., Khan, M. H., Hayat, M., Khan, F. S., & Fu, H. (2023) · Medical Image Analysis · doi:10.1016/j.media.2023.102802 · Cited by 1,506
“LAT [260] Eye Fundus 2D Messidor-1 [261] Messidor-2 [261] EyePACS [262] AuC Kappa Hybrid Formulate lesion discovery as a weakly supervised lesion localization problem via a transformer decoder.”
BackgroundPorwal, P., Pachade, S., Kamble, R. M., Kokare, M., Deshmukh, G., Sahasrabuddhe, V., & Mériaudeau, F. (2018) · Data · doi:10.3390/data3030025 · Cited by 932
“The diabetic retinal images were classified into separate groups ranging from 0 (No apparent DR) to 4 (Severe DR) according to the International Clinical Diabetic Retinopathy Scale [24], similar to existing Kaggle DR Dataset [25].”
MethodKrause, J., Gulshan, V., Rahimy, E., Karth, P., Widner, K., Corrado, G. S., Peng, L., & Webster, D. R. (2018) · Ophthalmology · doi:10.1016/j.ophtha.2018.01.034 · Cited by 564
Deep image mining for diabetic retinopathy screening
Quellec, G., Charrière, K., Boudi, Y., Cochener, B., & Lamard, M. (2017) · Medical Image Analysis · doi:10.1016/j.media.2017.04.012 · Cited by 537
Metadata
- Authors
- Cuadros, J., & Bresnick, G.
- Affiliations
- University of California, Berkeley (US)
- Corresponding author
- Cuadros, Jorge
- Venue
- Journal of Diabetes Science and Technology
- Publisher
- SAGE Publications
- Published
- 2009-05
- Volume
- 3
- Issue
- 3
- Pages
- 509-516
- ISSN
- 1932-2968 (ISSN-L)
- PMC
- PMC2769884
- OpenAlex
- W2115531174
- Cited by
- 390
- References
- 27
- Citations by year
- 2026: 38 · 2025: 30 · 2024: 48 · 2023: 53 · 2022: 47 · 2021: 43 · 2020: 38 · 2019: 19 · 2018: 17 · 2017: 6 · 2016: 11 · 2015: 11 · 2014: 6 · 2013: 7 · 2012: 5
- FWCI
- 4.03
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Journal of Diabetes Science and Technology (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Retinal Imaging and Analysis
- Health Sciences › Medicine › Ophthalmology › Ophthalmology and Visual Health Research
- Health Sciences › Medicine › Ophthalmology › Retinal Diseases and Treatments
- Keywords
- diabetic retinopathy screening, telemedicine, EyePACS, primary care, retinopathy grading, referral rates, electronic health record integration, Health Level 7, chronic disease registry
- MeSH terms
- Diabetic Retinopathy, Humans, Mass Screening, Referral and Consultation, Retrospective Studies, Severity of Illness Index, Software, Telemedicine, Remote Consultation, Internet, Electronic Health Records
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
