NCT06582407View on ClinicalTrials.gov

Machine Learning Models for Predicting Unforeseen Hospital Admissions or Discharges After Anesthesia

CompletedOBSERVATIONAL
Enrollment

68,683

Participants

Timeline

Start Date

January 1, 2020

Primary Completion Date

June 30, 2024

Study Completion Date

July 30, 2024

Conditions
Anesthesia ComplicationSurgery-ComplicationsPain, Postoperative
Interventions
OTHER

Mathematical Prediction of unforseen patient reorientation

The goal of this project is to develop models to predict in the preoperative period which patients will require hospital admission after ambulatory surgery or unforeseen hospital discharge after surgery

Trial Locations (1)

7000

Université de Mons, Mons

All Listed Sponsors
lead

HUmani

NETWORK

NCT06582407 - Machine Learning Models for Predicting Unforeseen Hospital Admissions or Discharges After Anesthesia | Biotech Hunter | Biotech Hunter