Natural occurrence of nocturnal hypoglycemia detection using hybrid particle swarm optimized fuzzy reasoning model

Artificial Intelligence in Medicine

Volumn 55, Issue 3, 2012, Pages 177-184

  Ling, Sai Ho ^a   Nguyen, Hung T ^a  

^a UNIVERSITY OF TECHNOLOGY SYDNEY   (Australia)

Author keywords

Fuzzy reasoning model; Hypoglycemia detection; Particle swarm optimization

Indexed keywords

BLOOD GLUCOSE; CLINICAL STUDY; DATA POINTS; DATA SETS; DEPARTMENT OF HEALTHS; ELECTROCARDIOGRAM SIGNAL; FITNESS FUNCTIONS; FUZZY REASONING; HEART RATES; HYBRID PARTICLES; INSULIN THERAPY; MUTATION OPERATIONS; PHYSIOLOGICAL PARAMETERS; SAMPLING TIME; SIDE EFFECT; TESTING PERFORMANCE; TRAINING PROCESS; TRAINING SETS; TYPE 1 DIABETES MELLITUS; WESTERN AUSTRALIA;

ALGORITHMS; ELECTROCARDIOGRAPHY; GLUCOSE; HEART; INSULIN; OPTIMIZATION; PHYSIOLOGICAL MODELS;

PATIENT TREATMENT;

GLUCOSE;

ADOLESCENT; ARTICLE; BLOOD GLUCOSE MONITORING; CLINICAL ARTICLE; CONTROLLED STUDY; ELECTROCARDIOGRAPHY; FUZZY LOGIC; GLUCOSE BLOOD LEVEL; HEART RATE; HUMAN; HYBRID; INSULIN DEPENDENT DIABETES MELLITUS; MUTATION; NOCTURNAL HYPOGLYCEMIA; PRIORITY JOURNAL; QT INTERVAL; SENSITIVITY AND SPECIFICITY;

ADOLESCENT; ALGORITHMS; ARTIFICIAL INTELLIGENCE; BLOOD GLUCOSE; DIABETES MELLITUS, TYPE 1; ELECTROCARDIOGRAPHY; FUZZY LOGIC; HEART RATE; HUMANS; HYPOGLYCEMIA; HYPOGLYCEMIC AGENTS; INSULIN; SENSITIVITY AND SPECIFICITY;

EID: 84863776233     PISSN: 09333657     EISSN: 18732860     Source Type: Journal    
DOI: 10.1016/j.artmed.2012.04.003     Document Type: Article

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