Developing an AI model for personalized medicine in acute respiratory failure
Official title: A Clinical Study for Developing AI-based Clustering Model for Personalized Medicine in Acute Respiratory Failure: Single Center, Prospective Cohort Study
Run by Samsung Medical Center · NCT06479421 · Data updated 2026-11-12
This study is trying to create a new AI tool that helps doctors understand different types of patients with acute respiratory failure in the ICU and how they might respond to treatment.
Quick facts
| Study type | Observational |
|---|---|
| Ages | 18 Years and up |
| Sex | All |
| Enrollment | 250 (estimated) |
| Sponsor | Samsung Medical Center Academic / other |
| Locations | 1 site (Seoul, Gangnam) |
| Status | Recruiting |
| Started | August 14, 2023 |
| Main results expected | April 30, 2028 |
| Study ends | April 30, 2029 |
| Registry record updated | April 28, 2026 |
| Trial ID | NCT06479421 on ClinicalTrials.gov |
Is this trial a fit for you?
✓Likely a good fit
Ideal candidates include adults aged 18 or older who require advanced respiratory support due to acute respiratory failure.
✕Probably not a fit
Patients who do not require high flow nasal cannula, non-invasive ventilation, or mechanical ventilation will not benefit from this study.
A plain-English reading of the study's rules. Only the study team can confirm whether you qualify.
What this trial studies
This study aims to collect clinical information from patients with acute respiratory failure admitted to the intensive care unit, specifically those requiring high flow nasal cannula, non-invasive ventilation, or mechanical ventilation. It will also include a control group of patients without acute respiratory failure for comparative analysis. The goal is to develop a clustering analysis model to identify phenotypes and assess clinical characteristics and prognosis. This observational study will help in understanding the different patient profiles and their outcomes.
Why it matters
Potential benefit: If successful, this study could lead to more personalized treatment strategies for patients with acute respiratory failure.
How similar studies have gone: While the use of AI in clustering and phenotyping is gaining traction, this specific approach in acute respiratory failure is relatively novel and has not been extensively tested.
Who can join: the full rules
Show full inclusion / exclusion criteria
\# Inclusion Criteria: \- Acute Respiratory Failure group Among patients admitted to the internal medicine intensive care unit at Samsung Seoul Hospital, if all of the following conditions are met: 1\) Age 18 or older 2) Patients who require treatment with high flow nasal cannula (HFNC), non-invasive ventilation (NIV (BIPAP or CPAP)), or mechanical ventilation (MV) due to acute respiratory failure. \- control group For comparative analysis, among patients admitted to the internal medicine intensive care unit at Samsung Seoul Hospital who meet all of the following conditions, they are registered as a control group with the consent of the subjects and undergo the same research procedure. 1. Age 18 or older 2. Patients who do not require high flow nasal cannula (HFNC), non-invasive ventilation (NIV (BIPAP or CPAP)), or mechanical ventilation (MV) treatment * Exclusion Criteria: If any of the following criteria applies, participants will not be permitted to participate in this clinical trial. 1. Patients 48 hours after oxygen treatment (HFNC, NIV (BIPAP or CPAP), MV) 2. Patients transferred from another hospital 3. Patients with limitations in treatment
Where it's running
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Samsung Medical Center
Seoul, Gangnam, South Korea Recruiting
Study contacts
- Study coordinator: Ryoung Eun Ko, MD, PhD
- Email: koryoungeun@gmail.com
- Phone: +82-2-3410-6399
Similar studies
Other studies for the same condition or treatment. Recruiting studies are listed first.
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How to take part
- Review the eligibility criteria above with your treating physician.
- Check the official listing on ClinicalTrials.gov for the latest contact details and recruitment status.
- Contact the study coordinator or principal investigator to ask for pre-screening. Pre-screening is free and never obligates you to enroll.