AMERICAN JOURNAL OF RESPIRATORY AND CRITICAL CARE MEDICINE, cilt.188, sa.11, ss.1303-1312, 2013 (SCI İndekslerine Giren Dergi)
Makale / Tam Makale
AMERICAN JOURNAL OF RESPIRATORY AND CRITICAL CARE MEDICINE
Rationale: Unsupervised statistical learning techniques, such as exploratory factor analysis (EFA) and hierarchical clustering (HC), have been used to identify asthma phenotypes, with partly consistent results. Some of the inconsistency is caused by the variable selection and demographic and clinical differences among study populations.