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Slit-lamp images are widely used in ophthalmology for the detection of cataract, keratopathy and other anterior segment disorders. In real-world practice, the quality of slit-lamp images can be unacceptable, which can undermine diagnostic accuracy and efficiency. Here, the researchers established and validated an artificial intelligence system to achieve automatic quality assessment of slit-lamp images upon capture. This system can also provide guidance to photographers according to the reasons for low quality.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Slit-lamp image quality assessment | Device: an artificial intelligence system for quality assessment of slit-lamp images. These patients are enrolled in primary healthcare units or the AI clinic at Zhongshan Ophthalmic Center |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Taking slit-lamp images | Device | The participant only needs to take several slit-lamp images as usual. |
|
| Measure | Description | Time Frame |
|---|---|---|
| Performance of artificial intelligence system for distinguish between good image quality and poor image quality | Area under the receiver operating characteristic curves, sensitivity, specificity, positive and negative predictive values,accuracy | 3 months |
| Measure | Description | Time Frame |
|---|---|---|
| The comparison of the performance for previous artificial intelligence diagnostic system with slit-lamp images of different image quality | Cohen's kappa coefficient, P value and other related statistic results | 3 months |
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Inclusion Criteria:
Exclusion Criteria:
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Inclusion Criteria: - Patients should be aware of the contents and signed for the informed consent. Exclusion Criteria: - 1. Patients who cannot cooperate with a photographer such as some paralytics, the patients with dementia and severe psychopaths. - 2. Patients who do not agree to sign informed consent
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| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Zhongshan Ophthalmic Center, Sun Yat-sen University | Guangzhou | Guangdong | 510060 | China |
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