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This study is being done to evaluate the performance of a software that uses artificial intelligence to analyze photographs of the retina to help detect diabetic retinopathy. The study will also assess the safety of the software in combination with a fundus camera already available on the market. This software analyzes retinal photographs to detect more than mild diabetic retinopathy in adults with diabetes. The results will be compared to expert human evaluations.
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| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| automatic analysis of fundus images performed by the software tool based on artificial intelligence | Device | the duration of the intervention is the analysis performed by the software tool based on fundus images acquired |
| Measure | Description | Time Frame |
|---|---|---|
| Number of subjects whose results provided by the automatic AI-based tool match the reading center grading for the identification of referable diabetic eye disease (more than mild DR). | 1-day visit |
| Measure | Description | Time Frame |
|---|---|---|
| percentage of eyes for which the AI-based automatic tool produced a result | 1-day visit |
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Inclusion Criteria:
Exclusion Criteria:
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population attending a primary-care facility with diagnosis of diabetes mellitus and/or past diagnosis of diabetic retinopathy
| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Rui | Contact | 00393357442593 | chiara.rui@icare-world.com | |
| Rumiato | Contact | ra.imaging@icare-world.com |
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| ID | Term |
|---|---|
| D003930 | Diabetic Retinopathy |
| ID | Term |
|---|---|
| D012164 | Retinal Diseases |
| D005128 | Eye Diseases |
| D003925 | Diabetic Angiopathies |
| D014652 | Vascular Diseases |
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| D002318 |
| Cardiovascular Diseases |
| D048909 | Diabetes Complications |
| D003920 | Diabetes Mellitus |
| D004700 | Endocrine System Diseases |