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ER-VISION-AI Study

NCT07727590 · Status: NOT_YET_RECRUITING · Phase: NA · Type: INTERVENTIONAL · Enrollment: 1000

Last updated 2026-07-27

No results posted yet for this study

Summary

Prospective, multicenter, randomized, open-label, blinded-endpoint (PROBE-like) clinical trial evaluating whether physician-supervised Generative Pre-trained Transformer (GPT)-assisted multimodal diagnostic support improves diagnostic concordance in emergency department patients presenting with acute cardiopulmonary symptoms.

Conditions

Interventions

DIAGNOSTIC_TEST

Generative Pre-trained Transformer (GPT)-assisted multimodal visual language model (VLM) diagnostic support

A Generative Pre-trained Transformer (GPT)-based multimodal visual language model integrates electrocardiograms, chest radiographs, structured clinical information, laboratory findings, vital signs, and relevant clinical history to generate diagnostic suggestions and differential diagnoses for physician-supervised clinical decision support.

DIAGNOSTIC_TEST

Conventional emergency department diagnostic evaluation

Routine emergency department diagnostic evaluation performed according to standard clinical practice without AI-assisted diagnostic support.

Sponsors & Collaborators

  • Ewha Womans University Seoul Hospital

    collaborator OTHER

  • Ewha Womans University Mokdong Hospital

    lead OTHER

Study Design

Allocation
RANDOMIZED
Purpose
DIAGNOSTIC
Masking
NONE
Model
PARALLEL

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2027-01-01
Primary Completion
2028-12-31
Completion
2029-12-31

Countries

  • South Korea

Study Locations

More Related Trials

Entities

Diseases

Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT07727590 on ClinicalTrials.gov