ArticleIndian journal of ophthalmology2014
Automated diabetic retinopathy imaging in Indian eyes: a pilot study.
Article in Indian journal of ophthalmology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 7 papers, 1 of them a synthesis that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
7 citing papers in PubMed, 1 synthesis or guideline pooled it, 17 citations in OpenAlex.
- Five regions, five retinopathy screening programmes: a systematic review of how Portugal addresses the challenge.BMC health services research · 2021Pooled it
- A Feasibility Study of Diabetic Retinopathy Detection in Type II Diabetic Patients Based on Explainable Artificial Intelligence.Journal of medical systems · 2023Article
- Variability in Grading Diabetic Retinopathy Using Retinal Photography and Its Comparison with an Automated Deep Learning Diabetic Retinopathy Screening Software.Healthcare (Basel, Switzerland) · 2023Article
- Capacity building for diabetic retinopathy screening by optometrists in India: Model description and pilot results.Indian journal of ophthalmology · 2021Article
- Medios- An offline, smartphone-based artificial intelligence algorithm for the diagnosis of diabetic retinopathy.Indian journal of ophthalmology · 2020Observational
- Screening for diabetic retinopathy: New methods to come.Indian journal of ophthalmology · 2016Article
- Automated diabetic retinopathy imaging in Indian eyes: a pilot study: erratum.Indian journal of ophthalmology · 2015Article
Corrections and comments
- Erratum issuedAutomated diabetic retinopathy imaging in Indian eyes: a pilot study: erratum.2015 · Lob, Aneesha [corrected to Lobo, Aneesha]
Authors and funding
7 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
aimTo evaluate the efficacy of an automated retinal image grading system in diabetic retinopathy (DR) screening. MATERIALS AND
methodsColor fundus images of patients of a DR screening project were analyzed for the purpose of the study. For each eye two set of images were acquired, one centerd on the disk and the other centerd on the macula. All images were processed by automated DR screening software (Retmarker). The results were compared to ophthalmologist grading of the same set of photographs.
results5780 images of 1445 patients were analyzed. Patients were screened into two categories DR or no DR. Image quality was high, medium and low in 71 (4.91%), 1117 (77.30%) and 257 (17.78%) patients respectively. Specificity and sensitivity for detecting DR in the high, medium and low group were (0.59, 0.91); (0.11, 0.95) and (0.93, 0.14).
conclusionAutomated retinal image screening system for DR had a high sensitivity in high and medium quality images. Automated DR grading software's hold promise in future screening programs.
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