NCT06843499

Effectiveness and Cost-Effectiveness Evaluations of AI-Assisted Diagnostic Software (VeriSee) for Ophthalmic Disease Screening

• Status: Recruiting
• Phase: N/A
• Study type: Interventional
• Enrollment: 1,000 (estimated)
• Sponsor: National Taiwan University Hospital · Academic / Other
• Sex: All
• Age: 20 Years
• Healthy volunteers: Not accepted

Summary

This study aims to evaluate the effectiveness of an artificial intelligence (AI)-assisted screening system in ophthalmic diagnosis. Using AI-based fundus photography, the system will assist physicians in diagnosing three common eye diseases: age-related macular degeneration and diabetic retinopathy (DR). The AI system will analyze fundus images from participants and rapidly generate detection results for ophthalmologists' reference in making final diagnoses and clinical decisions. The study will assess the clinical benefits of the AI-assisted diagnostic system, providing scientific evidence to enhance the efficiency of ophthalmic disease diagnosis and treatment.

Detailed description

Artificial Intelligence (AI) has shown significant potential in medical imaging analysis and disease diagnosis, particularly in ophthalmology. Substantial advancements have been made in utilizing AI for diagnosing common ophthalmic diseases, enhancing early detection and improving patient outcomes. Early diagnosis of age-related macular degeneration (AMD) and diabetic retinopathy (DR) is crucial for effective treatment and disease management. However, current clinical diagnoses rely heavily on ophthalmologists, leading to challenges such as low patient attendance rates and unequal distribution of diagnostic resources. To address these issues, this study will provide robust evidence to further validate the diagnostic performance of AI-assisted screening and clinical effectiveness of the VeriSee AI-assisted diagnostic system in the detection of diabetic DR and AMD. VeriSee AMD and VeriSee DR are AI-powered medical software tools designed to screen for AMD and DR, respectively. These systems employ advanced AI algorithms to analyze color fundus photography images, assess disease conditions, and evaluate image quality. By integrating this software into clinical workflows, physicians receive instant diagnostic support, improving efficiency and accessibility in ophthalmic disease screening.

Conditions

• Age-Related Macular Degeneration (AMD)
• Diabetic Retinopathy (DR)

Interventions

Type	Name	Description
OTHER	The VeriSee AI-assisted diagnostic system	VeriSee AMD, VeriSee DR, and VeriSee GLC are AI-based medical software devices designed for screening age-related macular degeneration (AMD), diabetic retinopathy (DR), and glaucoma, respectively. These systems utilize advanced AI algorithms to analyze color fundus photography images for disease assessment. By installing the software on a computer, the system can evaluate image quality, predict disease conditions, and instantly provide results to clinical physicians, serving as a diagnostic aid.
OTHER	Data collection from the patient's clinical history	Data collection from the patient's clinical history was conducted because the VeriSee AI-assisted diagnostic system was not used.

Timeline

• Start date: 2025-06-02
• Primary completion: 2027-12-31
• Completion: 2027-12-31
• First posted: 2025-02-25
• Last updated: 2025-06-22

Locations

1 site across 1 country: Taiwan