Machine learning-based spirometry reference values for the Iranian population: a cross-sectional study from the Shahedieh PERSIAN cohort.

ABSTRACT:

Objective

This study aimed to determine spirometric norm values for the healthy Iranian adult population and compare them with established norm equations, specifically the GLI-Caucasian and Iranian equations.

Methods

During the recruitment phase of the Shahedieh Prospective Epidemiological Research Studies in Iran (PERSIAN) in 2016, spirometric parameters of 998 participants were obtained. KNN regression was used to extract reference values for spirometric parameters FEV₁, FVC, FEV₁/FVC, and FEF_25-75%, considering height and age as features. The performance of KNN regression was compared with conventional models used in previous studies, such as the multiple linear regression (MLR) model and the Lambda-Mu-Sigma (LMS) model. The predicted valu

SUBMITTER: Loeloe MS 

PROVIDER: S-EPMC11938426 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature