Supporting diagnostic decisions using hybrid and complementary data mining applications: A pilot study in the pediatric emergency department

Pediatric Research

Volumn 71, Issue 6, 2012, Pages 725-731

  Grigull, Lorenz ^a   Lechner, Werner M ^b  

^a HANNOVER MEDICAL SCHOOL   (Germany)

^b Data Mining Consulting   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

C REACTIVE PROTEIN;

ALGORITHM; APPENDICITIS; ARTICLE; ARTIFICIAL NEURAL NETWORK; BLOOD CELL COUNT; CHILD; CLINICAL FEATURE; COMPUTER ASSISTED DIAGNOSIS; COMPUTER PROGRAM; COMPUTER SYSTEM; CONTROLLED STUDY; DATA MINING; DIAGNOSTIC ACCURACY; DIAGNOSTIC TEST; EMERGENCY WARD; ERYTHROBLASTOPENIA; FUZZY LOGIC; HUMAN; IDIOPATHIC THROMBOCYTOPENIC PURPURA; LABORATORY TEST; MAJOR CLINICAL STUDY; MEDICAL DECISION MAKING; PARAMETERS; PEDIATRIC EMERGENCY DEPARTMENT; PILOT STUDY; PNEUMONIA; PRIORITY JOURNAL; PROTEIN BLOOD LEVEL; SUPPORT VECTOR MACHINE; VOTING ALGORITHM;

ALGORITHMS; APPENDICITIS; CHILD; CHILD, PRESCHOOL; COHORT STUDIES; DATA MINING; DECISION SUPPORT SYSTEMS, CLINICAL; DIAGNOSIS, COMPUTER-ASSISTED; EMERGENCY SERVICE, HOSPITAL; FUZZY LOGIC; HUMANS; NEURAL NETWORKS (COMPUTER); PEDIATRICS; PILOT PROJECTS; PNEUMONIA; PROSPECTIVE STUDIES; PURPURA, THROMBOCYTOPENIC, IDIOPATHIC; RETROSPECTIVE STUDIES; SUPPORT VECTOR MACHINES;

EID: 84861361894     PISSN: 00313998     EISSN: 15300447     Source Type: Journal    
DOI: 10.1038/pr.2012.34     Document Type: Article

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