Artificial Intelligence System for Assessing Image Quality of Slit-Lamp Images and Its Effects on Diagnosis
- Conditions
- Artificial IntelligenceAnterior Segment Disorders
- Registration Number
- NCT04314180
- Lead Sponsor
- Sun Yat-sen University
- Brief Summary
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.
- Detailed Description
Not available
Recruitment & Eligibility
- Status
- UNKNOWN
- Sex
- All
- Target Recruitment
- 300
- Patients should be aware of the contents and signed for the informed consent.
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- Patients who cannot cooperate with a photographer such as some paralytics, the patients with dementia and severe psychopaths.
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- Patients who do not agree to sign informed consent.
Study & Design
- Study Type
- OBSERVATIONAL
- Study Design
- Not specified
- Primary Outcome Measures
Name Time Method Performance of artificial intelligence system for distinguish between good image quality and poor image quality 3 months Area under the receiver operating characteristic curves, sensitivity, specificity, positive and negative predictive values,accuracy
- Secondary Outcome Measures
Name Time Method The comparison of the performance for previous artificial intelligence diagnostic system with slit-lamp images of different image quality 3 months Cohen's kappa coefficient, P value and other related statistic results
Trial Locations
- Locations (1)
Zhongshan Ophthalmic Center, Sun Yat-sen University
🇨🇳Guangzhou, Guangdong, China
Zhongshan Ophthalmic Center, Sun Yat-sen University🇨🇳Guangzhou, Guangdong, China