A Multimodal AI Agent for Ophthalmic Clinical Decision Support
Trial statusNot yet recruiting
Trial phaseNot applicable
Trial typeInterventional
Biological sexAll
Age6-75
SponsorThe Hong Kong Polytechnic University
About this trial
This study is a multicenter randomized controlled trial evaluating the effectiveness and safety of EyeAgent, a multimodal artificial intelligence (AI) agent designed to assist ophthalmologists in clinical decision-making. Participants will be recruited from ophthalmology clinics and hospitals in Hong Kong and mainland China. The AI agent acts as a digital co-pilot, analyzing patient images and clinical history to provide diagnostic and management recommendations. The trial aims to determine whether the use of the AI agent improves diagnostic accuracy, treatment decision-making performance, report generation, workflow efficiency, and user satisfaction compared to standard clinical practice.
Eligibility criteria
This trial accepts healthy volunteersQualifiers
Outpatient participants aged 6 to 75 years.
Participants who undergo ophthalmic examinations for medical purposes during the study period.
Participants who can produce clear ophthalmic images in both eyes.
Participants aged 18 years or older provide their own consent.
Disqualifiers
Participants who are reluctant to participate in this study.
Participants presenting with acute or emergency ocular conditions requiring immediate intervention.
Participants with poor quality of ophthalmic images, including blurriness, artifacts, underexposure, or overexposure.
Other unsuitable reasons determined by the evaluators.
Trial design
Design model
Parallel
Treatments tested in this trial
EyeAgent AI system
DeviceEyeAgent is a multimodal AI agent assistant for ophthalmology that integrates imaging, electronic health records, and curated clinical knowledge. In this arm, EyeAgent supports clinicians in clinical consultation, including report generation, diagnostic interpretation, and treatment planning.
Treatment groups
300 Participants
are divided into 2 treatment groupsGroup A: AI-assisted care armExperimental treatment 1 intervention
Group B: Standard care armNo intervention 0 interventions
Trial outcomes
Primary outcomes
1
Diagnostic accuracy rate
Proportion of diagnoses consistent with a reference expert panel.
Time frame
Immediately after the intervention.2
Rate of inappropriate treatment decisions
The frequency of treatment recommendations (e.g., injection, laser therapy, or observation) that deviate from clinical guidelines as determined by the senior expert panel gold standard. Expert adjudication is conducted post-hoc after the enrollment phase concludes.
Time frame
Immediately after the intervention.Secondary outcomes
1
Report quality
Quality of clinical reports assessed using a structured Expert Report Quality Rubric evaluating five domains: accuracy, completeness, safety, reasoning, and interpretability. Each domain is scored on a 3-point scale (1 = poor, 2 = acceptable, 3 = good). Total scores range from 5 to 15. Higher scores indicate better report quality.
Time frame
Within 1 month after enrollment.2
Clinician confidence
Self-rated confidence in diagnosis and treatment planning measured using a single-item 5-point Likert scale (1 = not confident at all; 5 = extremely confident).
Time frame
Immediately after the intervention.3
Workflow efficiency
Time elapsed from image acquisition to final diagnosis and report completion.
Time frame
During the index diagnostic session.4
Satisfaction and usability
Usability of the AI agent assessed using the System Usability Scale (SUS), a validated 10-item questionnaire scored on a 5-point Likert scale. Each item is scored from 1 (Strongly disagree) to 5 (Strongly agree). Total SUS scores are calculated according to standard scoring procedures and range from 0 to 100, with higher scores indicating better perceived usability.
Time frame
At the end of each clinician's participation period, approximately 2 months.Sponsors and contacts
Click on the lead sponsor to view all of their trials.
Source ClinicalTrials.gov
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