Description Module

Description Module

The Description Module contains narrative descriptions of the clinical trial, including a brief summary and detailed description. These descriptions provide important information about the study's purpose, methodology, and key details in language accessible to both researchers and the general public.

Description Module path is as follows:

Study -> Protocol Section -> Description Module

Description Module


Ignite Creation Date: 2026-03-26 @ 3:14 PM
Ignite Modification Date: 2026-03-26 @ 3:14 PM
NCT ID: NCT07401459
Brief Summary: 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.
Detailed Description: This multicenter, randomized controlled trial aims to evaluate the integration of EyeAgent, a multimodal artificial intelligence (AI) agent, in real-world clinical settings. The AI system is designed to support clinicians by analyzing patient data, including ocular images and electronic health records, to aid in image interpretation, diagnosis, and treatment planning. A total of 300 participants will be randomly assigned to either an AI-assisted care arm or a standard care arm. In the AI-assisted arm, clinicians review the comprehensive report generated by AI agent as a supportive tool before finalizing their independent decisions. The study comprehensively measures diagnostic accuracy, the rate of inappropriate treatment decisions, report generation, workflow efficiency, and user questionnaire. By comparing these two groups, the trial aims to provide robust evidence on the effectiveness and practical utility of AI-driven clinical decision support in ophthalmology, with the goal of enhancing both the quality and efficiency of patient care.
Study: NCT07401459
Study Brief:
Protocol Section: NCT07401459