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.