Den här översättningen är inte klar ännu. Den här sidan är just nu på engelska.

Gå till den engelska sidan

Cure My Disease

Don't miss your cure!

 Log in / Sign up

AI could sharpen emergency diagnoses for chest pain and breathing trouble

NCT ID NCT07727590

Diagnosis Sponsor: Ewha Womans University Mokdong Hospital Source: ClinicalTrials.gov ↗

What the study statuses mean

This study's is highlighted.

Recruitment status, easiest to join first

Recruiting now
This trial is taking on new participants right now.
Not yet recruiting This study
Registered, but not yet taking participants.
By invitation only
Not open to general applications. Only people the study team invites can take part.
Paused
Paused for now. It may or may not start again.
Ongoing
Running, but no longer taking on new participants.
Completed
The trial has finished. Results may not be published yet.
Stopped early
Stopped early, before it reached the end. That can be for many reasons, including safety.
Cancelled
Cancelled before anyone took part.

Expanded access (not trials)

Expanded access
Not a trial. This treatment can be requested outside a study, case by case, for people who qualify.
Expanded access (paused)
Not a trial. The treatment can normally be requested outside a study, but is unavailable right now.
Expanded access (ended)
Not a trial. The treatment could once be requested outside a study, but no longer can.
Approved
The treatment has been approved, so it is available normally rather than through this programme.

When the status isn't known

Details not published
The full record has not been published yet, so there is little to show here.
Status unknown
This status has not been confirmed recently, so it may be out of date.

First seen Jul 27, 2026 · Last updated Jul 28, 2026 · Updated 1 time

Summary

This trial tests whether an artificial intelligence tool can help emergency room doctors better diagnose patients with chest pain, shortness of breath, or other acute heart and lung symptoms. The AI analyzes ECGs, chest X-rays, lab results, and patient history to suggest possible diagnoses. About 1,000 adults across multiple hospitals will be randomly assigned to receive either standard care or AI-assisted diagnosis. The goal is to see if the AI improves how often the emergency diagnosis matches the final confirmed diagnosis.

What this could mean

Our plain-language read of the trial. This is informational only, not medical advice or a prediction.

Active substance
A GPT-based multimodal visual language model that analyzes ECGs, chest X-rays, lab results, and patient history to suggest diagnoses.
What this could lead to
If successful, this AI tool could help emergency doctors make faster, more accurate diagnoses for common but serious symptoms like chest pain and shortness of breath.
What could go wrong
The AI may not improve accuracy in real-world emergency settings, could produce errors, or may not work equally well for all patient groups. This is an early-stage trial.

This is an AI summary of the original study and may miss details. Read our disclaimer.

Study facts

What this study's own registry entry says, in plain language.

Phase

Not a phased trial

Phase numbers describe drug development. The registry uses this when they do not apply, as it does for trials of devices, procedures or behaviour changes, and for observational studies.

Participants

About 1,000 people

The number the study aims to enrol. It can still change while the study runs.

Expected to start

Jan 2027

An estimate. Start dates often move.

Expected to finish

Dec 2029

An estimate. End dates often move.

Lead sponsor

Other sponsor

The registry's catch-all category, for sponsors it does not file as a company, a government agency, or a research network.

Who can take part

This study's own entry requirements. Only the study team can say for certain whether you qualify.

Ages

18 years and older

Sex

Anyone

Healthy volunteers

Not accepted

This study is not open to healthy volunteers. The entry requirements below say who it is open to.

Show the full entry requirements

Copied word for word from the study's registry entry, so the wording is the study team's rather than ours.

Inclusion Criteria: * Age ≥18 years * Presentation to a participating emergency department with acute cardiopulmonary symptoms, including chest pain, dyspnea, palpitations, syncope, dizziness, or fever accompanied by cardiopulmonary symptoms * Performance of both a standard 12-lead electrocardiogram and chest radiography during the initial emergency department evaluation * Availability of initial clinical assessment, vital signs, laboratory findings, and all mandatory clinical information required for the multimodal AI workflow * Expected emergency department observation or hospital admission for at least 24 hours * Ability and willingness to provide written informed consent Exclusion Criteria: * Inability or refusal to provide written informed consent * Requirement for immediate life-saving intervention that precludes completion of the study workflow * Death before completion of the initial emergency department diagnostic assessment * Electrocardiographic quality insufficient for reliable physician or Artificial intelligence (AI) interpretation * Chest radiographic quality insufficient for reliable physician or Artificial intelligence (AI) interpretation * Cardiac pacing rhythm * Missing mandatory clinical information required for the multimodal Artificial intelligence (AI) workflow * Previous enrollment in the ER-VISION-AI trial * Inability to establish a blinded adjudicated reference diagnosis

Get updates

Get notified about this study

Sign up to get updates when this study changes or when new studies for Acute cardiopulmonary disease are added.

Vår säkerhetsrekommendation!

Genom att skicka in godkänner du våra Användarvillkor

Conditions

The condition(s) this trial relates to.

Chest Pain Dyspnea Emergencies

As listed by the trial registrant

The condition terms exactly as the trial's registrant entered them.

Acute cardiopulmonary disease Chest pain Dyspnea Emergency department patients

How to take part

Only the study team decides who joins. These are the ways to reach them.

  1. The places running it

    1 site. The list below names each one and where it is.

  2. The official record

    ClinicalTrials.gov lists the study team's own contact details, including names and phone numbers. We don't republish those.

    Open the record ↗

  3. A doctor treating you

    A doctor who knows your case can contact a study site on your behalf, and can tell you whether this study is worth pursuing at all.

Contacts and locations

Locations

  • Ewha Womans University Mokdong Hospital

    Seoul, 07804, South Korea

More trials for these conditions

Other studies related to the condition(s) this trial covers.