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

National Taiwan University

Status: Enrolling

Conditions: Diabetic Retinopathy (DR); Age-Related Macular Degeneration (AMD)

Treatments: Other: The VeriSee AI-assisted diagnostic system; Other: Data collection from the patient's clinical history

Study type: Interventional

Funder types: Other

Identifiers

NCT06843499

202412086DINC

Details and patient eligibility

About

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.

Full 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.

Enrollment: 1,000 estimated patients

Sex: All

Ages: 20+ years old

Volunteers: No Healthy Volunteers

Inclusion criteria

• VeriSee AMD is used in non-retinal subspecialty ophthalmology clinics for adults aged 50 and above.
• VeriSee DR is used in non-retinal subspecialty clinics for diabetic patients aged 20 and above.

Exclusion criteria

• The patient does not agree to participate in the trial or is unable to provide informed consent.

Trial design

Primary purpose: Screening

Allocation: N/A

Interventional model: Single Group Assignment

Masking: None (Open label)

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1,000 participants in 1 patient group

AI Intervention

Other group

Description:

Patients will undergo fundus photography screening using artificial intelligence-assisted diagnostic software (VeriSee). Ophthalmologists will independently interpret the same images, and the results will be compared with those generated by the AI.

Treatment:

Other: Data collection from the patient's clinical history

Other: The VeriSee AI-assisted diagnostic system