NCT06333002View on ClinicalTrials.gov

Machine Learning Model to Predict Outcome in Acute Hypoxemic Respiratory Failure

Active, not recruitingOBSERVATIONAL
Enrollment

1,241

Participants

Timeline

Start Date

March 19, 2024

Primary Completion Date

May 30, 2026

Study Completion Date

May 30, 2026

Conditions
Acute Hypoxemic Respiratory Failure
Interventions
OTHER

machine learning analysis

We will use robust machine learning approaches, such as Random Forest, Extreme Gradient Boosting, Support Vector Machine and Multilayer Perceptron.

Trial Locations (8)

3012

Hospital Universitario Virgen de Arrixaca, Murcia

13005

Hospital General Universitario de Ciudad Real, Ciudad Real

16002

Hospital Virgen de La Luz, Cuenca

28046

Hospital Universitario La Paz, Madrid

28222

Hospital Universitario Puerta de Hierro, Madrid

38010

Hospital Universitario NS de Candelaria, Santa Cruz de Tenerife

46010

Hospital Cinico de Valencia, Valencia

47012

Hospital Universitario Rio Hortega, Valladolid

All Listed Sponsors
lead

Dr. Negrin University Hospital

OTHER

NCT06333002 - Machine Learning Model to Predict Outcome in Acute Hypoxemic Respiratory Failure | Biotech Hunter | Biotech Hunter