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

Trial statusRecruiting
Trial phaseNot listed
Trial typeObservational
Biological sexAll
Age18+
SponsorUniversity of Oslo

About this trial

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 criteria

Qualifiers

elective hospitalisation for control of non-invasive ventilation

use of ResMedLumis 100/150 ventilator

treatment for >3 months

Disqualifiers

current exacerbation

Trial design

Treatments tested in this trial

  • Not listed

Trial groups

No trial groups listed

Sponsors and collaborators

University of Oslo

Lead sponsor

Oslo University Hospital

Collaborator