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NCT Number: NCT06843499

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

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.

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Key information

Conditions

Age-related Macular Degeneration (AMD) Cardiovascular Diseases Diabetes Complications Diabetes Mellitus Diabetic Angiopathies Diabetic Retinopathy Diabetic Retinopathy (DR) Endocrine System Diseases Eye Diseases Macular Degeneration Retinal Degeneration Retinal Diseases Vascular Diseases

Age range

20 year and older

Sex eligibility

All sexes

Study type

Interventional

Phase

Not applicable

Primary location

National Taiwan University Hospital

Taipei, Taiwan, 100225

Location status: Recruiting

Location contact

Yi-Ting Hsieh, Medical Doctor

CONTACT

[email protected]

+886-2-2312-3456 ext. 265018

About this study

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.

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

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.

Treatment and study plan

The VeriSee AI-assisted diagnostic system

Other

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.

Data collection from the patient's clinical history

Other

Data collection from the patient's clinical history was conducted because the VeriSee AI-assisted diagnostic system was not used.

Primary outcomes

  1. Sensitivity

    Time frame: From screening to physician-confirmed diagnosis of AMD or DR, an average of 1 month

    The sensitivity of the index test (VeriSee) was calculated as the proportion of participants with reference standard-confirmed disease who were correctly identified as positive by the AI-assisted diagnostic software.

  2. Specificity

    Time frame: From screening to physician-confirmed diagnosis of AMD or DR, an average of 1 month

    The specificity of the index test was calculated as the proportion of participants without the target condition, as determined by the reference standard, who were correctly classified as negative by the AI-assisted diagnostic tool.

  3. Concordance

    Time frame: From screening to physician-confirmed diagnosis of AMD or DR, an average of 1 month

    Concordance between the AI-assisted diagnosis and the ophthalmologists' interpretation was assessed using the overall agreement rate (i.e., the percentage of cases with identical classification results).

Secondary outcomes

  1. Total Cost Analysis (Including Direct and Indirect Costs)

    Time frame: From enrollment to 12 months after screening

    This measure includes direct medical costs (e.g., screening, follow-up, medication, and treatment), healthcare-related indirect medical costs (e.g., IT system maintenance, healthcare personnel), and non-medical indirect costs (e.g., transportation and productivity loss due to blindness). Costs will be analyzed from both the National Health Insurance perspective and the broader societal perspective.

Sponsors and collaborators

Lead sponsor

National Taiwan University Hospital

Other

Collaborators

  • Fu Jen Catholic University Hospital
  • Min-Sheng General Hospital
  • Ministry of Health and Welfare, Taiwan

Registry information

Important dates

Study start
2025
Primary completion
2027
Study completion
2027
First posted
Feb 25, 2025
Registry last updated
Jul 22, 2026

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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