Inferring characteristic phenotypes via class association rule mining in the bone dysplasia domain

Journal of Biomedical Informatics

Volumn 48, Issue , 2014, Pages 73-83

  Paul, Razan ^a   Groza, Tudor ^a   Hunter, Jane ^a   Zankl, Andreas ^b,c  

^a UNIVERSITY OF QUEENSLAND   (Australia)

^b UNIVERSITY OF QUEENSLAND   (Australia)

^c ROYAL BRISBANE AND WOMEN'S HOSPITAL   (Australia)

Author keywords

Bone dysplasias; Class association rule mining; Mining characteristic phenotypes

Indexed keywords

ALGORITHMS; BONE; INFERENCE ENGINES; ASSOCIATION RULES;

CLASS ASSOCIATION RULES; INFERENCE ALGORITHM;

DATA MINING;

ACCURACY; ALGORITHM; ARTICLE; BONE DYSPLASIA; CLASS ASSOCIATION RULE MINING; CLINICAL FEATURE; DATA MINING; HUMAN; INFERENTIAL STATISTICS; PHENOTYPE; PRIORITY JOURNAL; SENSITIVITY AND SPECIFICITY; AUTOMATION; BONE DISEASES, DEVELOPMENTAL; COMPUTER PROGRAM; FACTUAL DATABASE; INFORMATION RETRIEVAL; MEDICAL INFORMATICS; PATHOLOGY; PROCEDURES; REPRODUCIBILITY; CHARACTERISTIC FEATURE MINING ALGORITHM; CLASS ASSOCIATION RULE MINING ALGORITHM; CLASSIFICATION ALGORITHM; CONTROLLED STUDY; MEASUREMENT ACCURACY; MEASUREMENT PRECISION; VALIDATION STUDY;

ALGORITHMS; AUTOMATION; BONE DISEASES, DEVELOPMENTAL; DATA MINING; DATABASES, FACTUAL; HUMANS; INFORMATION STORAGE AND RETRIEVAL; MEDICAL INFORMATICS; PHENOTYPE; REPRODUCIBILITY OF RESULTS; SOFTWARE;

EID: 84899483170     PISSN: 15320464     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jbi.2013.12.001     Document Type: Article

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