Explorative data analysis techniques and unsupervised clustering methods to support clinical assessment of Chronic Obstructive Pulmonary Disease (COPD) phenotypes

Journal of Biomedical Informatics

Volumn 42, Issue 6, 2009, Pages 1013-1021

  Paoletti, Matteo ^a   Camiciottoli, Gianna ^a   Meoni, Eleonora ^a   Bigazzi, Francesca ^a   Cestelli, Lucia ^a   Pistolesi, Massimo ^a   Marchesi, Carlo ^a  

^a UNIVERSITY OF FLORENCE   (Italy)

Author keywords

Biomedical clustering; Biomedical data clustering; Biomedical data mining; Chronic Obstructive Pulmonary Disease; COPD; Explorative biomedical data analysis; Homogeneity analysis; K Harmonic Means; Multiple Correspondence Analysis; Principal Component Analysis

Indexed keywords

BIOMEDICAL CLUSTERING; BIOMEDICAL DATA CLUSTERING; BIOMEDICAL DATA MINING; CHRONIC OBSTRUCTIVE PULMONARY DISEASE; COPD; EXPLORATIVE BIOMEDICAL DATA ANALYSIS; HOMOGENEITY ANALYSIS; K-HARMONIC MEANS; MULTIPLE CORRESPONDENCE ANALYSIS;

CLUSTERING ALGORITHMS; COMPUTERIZED TOMOGRAPHY; PATHOLOGY; PRINCIPAL COMPONENT ANALYSIS;

CLUSTER ANALYSIS;

ARTICLE; CHRONIC OBSTRUCTIVE LUNG DISEASE; CIGARETTE SMOKING; CLINICAL ASSESSMENT; CLUSTER ANALYSIS; COMPUTER ASSISTED TOMOGRAPHY; DATA ANALYSIS SOFTWARE; DISEASE SEVERITY; HUMAN; MEDICAL INFORMATICS; PHENOTYPE; PRIORITY JOURNAL; RISK FACTOR; VALIDATION PROCESS;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; CLUSTER ANALYSIS; COMPUTATIONAL BIOLOGY; DATABASES, FACTUAL; HUMANS; MEDICAL INFORMATICS; PHENOTYPE; PRINCIPAL COMPONENT ANALYSIS; PULMONARY DISEASE, CHRONIC OBSTRUCTIVE; REPRODUCIBILITY OF RESULTS;

EID: 70350575210     PISSN: 15320464     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jbi.2009.05.008     Document Type: Article

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