Integrating regression formulas and kernel functions into locally adaptive knowledge-based neural networks: A case study on renal function evaluation

Artificial Intelligence in Medicine

Volumn 36, Issue 3, 2006, Pages 235-244

  Song, Qun ^a   Kasabov, Nikola ^a   Ma, Tianmin ^a,b   Marshall, Mark Roger ^b  

^a AUCKLAND UNIVERSITY OF TECHNOLOGY   (New Zealand)

^b MIDDLEMORE HOSPITAL   (New Zealand)

Author keywords

Glomerular filtration rate; Kernel functions; Knowledge based neural networks; Renal function evaluation

Indexed keywords

FUZZY SETS; KNOWLEDGE BASED SYSTEMS; MATHEMATICAL MODELS; MEDICAL APPLICATIONS;

GLOMERULAR FILTRATION RATE; KERNEL FUNCTIONS; KNOWLEDGE-BASED NEURAL NETWORKS; RENAL FUNCTION EVALUATION;

NEURAL NETWORKS;

ARTICLE; ARTIFICIAL NEURAL NETWORK; AUSTRALIA AND NEW ZEALAND; COMPARATIVE STUDY; GLOMERULUS FILTRATION RATE; HUMAN; KIDNEY FUNCTION; KIDNEY FUNCTION TEST; LEARNING; MATHEMATICAL MODEL; MEDICAL INFORMATICS; NONLINEAR REGRESSION ANALYSIS; NORMAL DISTRIBUTION; PHYSICIAN; PRIORITY JOURNAL; RACE DIFFERENCE;

ALGORITHMS; CREATININE; FEMALE; GLOMERULAR FILTRATION RATE; HUMANS; MALE; MIDDLE AGED; NEURAL NETWORKS (COMPUTER); REGRESSION ANALYSIS;

EID: 33644867270     PISSN: 09333657     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.artmed.2005.07.007     Document Type: Article

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