MedTrace Logo

From Bench to Bedside: A Machine Learning Tool for the Detection of Inspiratory Leak

NCT07428694 · Status: RECRUITING · Type: OBSERVATIONAL · Enrollment: 20

Last updated 2026-02-24

No results posted yet for this study

Summary

Study of the applicability of machine learning tools in detecting inspiratory leakage in longterm non-invasive ventilation. The study was conducted in two stages. Firstly the ML model was trained on both bench model created scenarios and then ten patients. And secondly the success of the model was assessed in a proof of concept pilot study of ten patients.

Conditions

  • Chronic Respiratory Failure

Sponsors & Collaborators

  • Oslo University Hospital

    collaborator OTHER

  • University of Oslo

    lead OTHER

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2025-10-01
Primary Completion
2026-10-01
Completion
2026-10-01

Countries

  • Norway

Study Locations

More Related Trials

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 NCT07428694 on ClinicalTrials.gov