Methods
Deep learning clustering was used to derive asthma phenotypes in a
sample of 1,895 subjects aged 16-75, drawn from the ongoing West Sweden
Asthma Study. The algorithm integrated 47 variables encompassing
demographics, risk factors, asthma triggers, pulmonary function, disease
severity, allergy, and comorbidity profiles. The optimal clustering
solution was selected by combining statistical metrics and clinical
interpretation.