Training machine learning-based spirometry reference equations: a comparison with GAMLSS and GLI reference equations
ML-derived spirometry equations demonstrated strong alignment with the observed data and outperformed global standards in representing Jordanian adults. These findings support the use of reference equations customized for specific regions in respiratory diagnostics.
Authors
- Judith Eberhardt (ORCID: https://orcid.org/0000-0003-0745-178X)
- Anan S. Jarab (ORCID: https://orcid.org/0000-0002-0416-506X)
- Walid A. Al-Qerem (ORCID: https://orcid.org/0000-0001-9831-7572)
Institutions
- Al-Zaytoonah University of Jordan (JO)
- Jordan University of Science and Technology (JO)
- Teesside University (GB)
Publication Details
- Journal
- European Clinical Respiratory Journal
- Published
- 2025-10-03
- DOI
- https://doi.org/10.1080/20018525.2025.2565853
- Primary Topic
- Chronic Obstructive Pulmonary Disease (COPD) Research
- Type
- article
- Field-Weighted Citation Impact
- 0.00