An observational study in Diabete Mellitus and Diabetic Retinopathy, sponsored by Zhongshan Ophthalmic Center, Sun Yat-sen University. Status unknown at 1 site in China. Per ClinicalTrials.gov, last updated 2019-04-02.
Sponsored by Zhongshan Ophthalmic Center, Sun Yat-sen University · Observational
This study is to build an multi-modal artificial intelligence ophthalmological imaging diagnostic system covering multi-level medical institutions. We are going to evaluate this system in an evidence-based medicine view, taking diabetic retinopathy as an example. And clinical diagnostic criteria will be made based on this multi-modal artificial intelligence imaging diagnostic system. The study is designed as a cross-sectional study involving 1,000 normal individuals, 1,000 diabetes patients without ocular complications, and 1,000 with diabetic ocular complications. Statistical analysis of the diagnostic sensitivity and specificity of the artificial intelligence system will be made, and ROC curve wil be draw.
815 studies on the registry are indexed under Retinal Diseases; 105 are open to participants now.
This study's planned enrollment of 3,000 is above the median of 180 across 282 observational studies indexed under Retinal Diseases.
Browse Retinal Diseases studies →Zhongshan Ophthalmic Center, Sun Yat-sen University is the lead sponsor of 159 studies on the registry; 77 are open to participants now.
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Stratified sampling
Group A(normal individuals): Meet all the items 1 \~ 5 below
Group B(diabetes patients without ocular complications): meet any of 1 to 3, and both 4 to 5 items
Group C(patients with diabetic ocular complications): meet with any of 1 to 3, and all 4 to 6 items
Exclusion Criteria:
The diagnostic sensitivity, specificity and ROC curve of the artificial intelligence(AI) system compared with reference standard (ophthalmologist).
Sensitivity: the percentage of diabetic retinopathy(DR) patients who are correctly identified as having the condition by AI. Sensitivity=True positive/(True positive+False negative). Specificity: the percentage of healthy people who are correctly identified as not having the condition by AI. Specificity=True negative /(True negative +False positive). The ROC curve was plotted with true positive rate (sensitivity) as the ordinate and false positive rate (1-specificity) as the abscissa.
Time frame: It will take 15~20min for each subject to take the exams.
This study is status unknown, as verified in Mar 2019. You cannot join it, but the record below documents what was studied.
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Zhongshan Ophthalmic Center, Sun Yat-sen University