Asthma is a heterogeneous disease comprising a number of subtypes which may be caused by different pathophysiologic mechanisms (sometimes referred to as endotypes) but may share similar observed characteristics (phenotypes). The use of unsupervised clustering in adult and paediatric populations has identified subtypes of asthma based on observable characteristics such as symptoms, lung function, atopy, eosinophilia, obesity, and age of onset. Here we describe different clustering methods and demonstrate their contributions to our understanding of the spectrum of asthma syndrome. Precise identification of asthma subtypes and their pathophysiological mechanisms may lead to stratification of patients, thus enabling more precise therapeutic and...
Current obstructive airways disease classification does not sufficiently reflect disease patterns. C...
Current obstructive airways disease classification does not sufficiently reflect disease patterns. C...
Asthma is increasingly recognised as an umbrella term to describe a number of distinct clinical pres...
Background: Data-driven methods such as hierarchical clustering (HC) and principal component analysi...
International audienceThere is a need to improve asthma characterisation by integrating multiple asp...
Background Data‐driven methods such as hierarchical clustering (HC) and principal component analysis...
BACKGROUND: Data-driven methods such as hierarchical clustering (HC) and principal component analysi...
ObjectiveThe heterogeneity of asthma has inspired widespread application of statistical clustering a...
Rationale: Unsupervised statistical learning techniques, such as exploratory factor analysis (EFA) a...
Objective: Asthma is divided into various distinct phenotypes on the basis of clinical characteristi...
Objective: Several diagnostic and treatment algorithms regarding asthma have been described in previ...
editorial reviewedIntroduction Eosinophilic asthma is well recognized asthma phenotype associated w...
Asthma is a heterogeneous disease with a range of observable phenotypes. To date, the characterizati...
Identification and characterization of asthma phenotypes are challenging due to disease complexity a...
<div><h3>Rationale</h3><p>Identification and characterization of asthma phenotypes are challenging d...
Current obstructive airways disease classification does not sufficiently reflect disease patterns. C...
Current obstructive airways disease classification does not sufficiently reflect disease patterns. C...
Asthma is increasingly recognised as an umbrella term to describe a number of distinct clinical pres...
Background: Data-driven methods such as hierarchical clustering (HC) and principal component analysi...
International audienceThere is a need to improve asthma characterisation by integrating multiple asp...
Background Data‐driven methods such as hierarchical clustering (HC) and principal component analysis...
BACKGROUND: Data-driven methods such as hierarchical clustering (HC) and principal component analysi...
ObjectiveThe heterogeneity of asthma has inspired widespread application of statistical clustering a...
Rationale: Unsupervised statistical learning techniques, such as exploratory factor analysis (EFA) a...
Objective: Asthma is divided into various distinct phenotypes on the basis of clinical characteristi...
Objective: Several diagnostic and treatment algorithms regarding asthma have been described in previ...
editorial reviewedIntroduction Eosinophilic asthma is well recognized asthma phenotype associated w...
Asthma is a heterogeneous disease with a range of observable phenotypes. To date, the characterizati...
Identification and characterization of asthma phenotypes are challenging due to disease complexity a...
<div><h3>Rationale</h3><p>Identification and characterization of asthma phenotypes are challenging d...
Current obstructive airways disease classification does not sufficiently reflect disease patterns. C...
Current obstructive airways disease classification does not sufficiently reflect disease patterns. C...
Asthma is increasingly recognised as an umbrella term to describe a number of distinct clinical pres...