RECRUITINGOBSERVATIONAL
Oscillometry and Machine Learning Approaches
Feasibility Study of Forced Oscillometry in the Prediction of Chronic Respiratory Diseases Using Machine Learning Approaches
About This Trial
Unicentric retrospective study designed to analyses the performance of various machine learning approaches to predict patterns of chronic respiratory diseases such as asthma, based mainly on clinical information and respiratory spirometry/oscillometry.
Who May Be Eligible (Plain English)
Who May Qualify:
- 18 - 90 years
- Spirometry available
- Confirmed clinical diagnosis of COPD, asthma, interstitial lung disease according to national or international guidelines
Who Should NOT Join This Trial:
- Acute respiratory infection
Always talk to your doctor about whether this trial is right for you.
Original Eligibility Criteria
View original clinical language
Inclusion Criteria:
* 18 - 90 years
* Spirometry available
* Confirmed clinical diagnosis of COPD, asthma, interstitial lung disease according to national or international guidelines
Exclusion Criteria:
* Acute respiratory infection
Treatments Being Tested
OTHER
1
Compare oscillometry results with spirometryClick to apply
Locations (1)
Hospital de la Santa Creu i Sant Pau
Barcelona, Spain