RecruitingNCT07428694
From Bench to Bedside: A Machine Learning Tool for the Detection of Inspiratory Leak
Sponsor
University of Oslo
Enrollment
20 participants
Start Date
Oct 1, 2025
Study Type
OBSERVATIONAL
Conditions
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.
Eligibility
Min Age: 18 Years
Inclusion Criteria3
- elective hospitalisation for control of non-invasive ventilation
- use of ResMedLumis 100/150 ventilator
- treatment for >3 months
Exclusion Criteria1
- current exacerbation
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Locations(1)
View Full Details on ClinicalTrials.gov
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NCT07428694
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