Effectiveness and Cost-Effectiveness Evaluations of AI-Assisted Diagnostic Software (VeriSee) for Ophthalmic Disease Screening
For patients and families
In plain language
An automatic summary of structured registry data. It is an orientation aid, not a substitute for the official protocol or a physician assessment.
- What is being studied
- The protocol lists: The VeriSee AI-assisted diagnostic system, Data collection from the patient's clinical history.
- Who it may be relevant to
- Registry conditions: Age-Related Macular Degeneration (AMD), Diabetic Retinopathy (DR). Basic parameters: from 20 years · All.
- What needs checking
- Age, condition and sex are only basic indicators. Prior treatment, laboratory values and other mandatory requirements appear in the eligibility criteria below.
- Where it takes place
- Taiwan
- Next step
- Save the trial, show it to the treating physician, and confirm current recruitment with the study center. Costs, documents and travel →
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Overview
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.
Interventions
- 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.
Primary outcome measures
- Sensitivity [Time frame: From screening to physician-confirmed diagnosis of AMD or DR, an average of 1 month]
- Specificity [Time frame: From screening to physician-confirmed diagnosis of AMD or DR, an average of 1 month]
- Concordance [Time frame: From screening to physician-confirmed diagnosis of AMD or DR, an average of 1 month]
Secondary outcome measures (1)
- Total Cost Analysis (Including Direct and Indirect Costs) [Time frame: From enrollment to 12 months after screening]
Eligibility criteria
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.
Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.
Healthy volunteers: No
Study design
- Allocation
- N/A
- Model
- Single group
- Masking
- Open label
- Primary purpose
- Screening
Study locations
Taiwan · 1 center
- National Taiwan University Hospital — Taipei
Identifiers
NCT: NCT06843499 · 202412086DINC