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

Recruitingn/aAges 18 Years - anyAllUniversity of Oslo
NCT07428694 on ClinicalTrials.gov ↗
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In plain words

What the trial is, and whether it could suit you

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.

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📋 Eligibility rules (as published)
Inclusion Criteria: * elective hospitalisation for control of non-invasive ventilation * use of ResMedLumis 100/150 ventilator * treatment for \>3 months Exclusion Criteria: * current exacerbation
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What it tests

  • Not listed
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Where

1 site
Oslo University Hospital
Oslo, Norway
🤝 Taking part is your choice, and you can leave at any time. Only the trial team can confirm you are eligible — always decide together with your own doctor.
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