Weka machine learning classification in identifying autonomic dysfunction parameters associated with ACE insertion/deletion genotypes

Proceedings of the 9th IASTED International Conference on Biomedical Engineering, BioMed 2012

Volumn , Issue , 2012, Pages 61-66

  Ng, Ethan ^a   Hambly, Brett ^a   Matthews, Slade ^a   McLachlan, Craig S ^b   Jelinek, Herbert F ^c,d  

^a UNIVERSITY OF SYDNEY   (Australia)

^b UNIVERSITY OF NEW SOUTH WALES   (Australia)

^c MACQUARIE UNIVERSITY   (Australia)

^d CHARLES STURT UNIVERSITY   (Australia)

Author keywords

ACE I D polymorphism; Autonomic dysfunction; Classification; Genotypes; Heart rate variability; Machine learning algorithms; Renin angiotensin system

Indexed keywords

AUTONOMIC DYSFUNCTION; AUTONOMIC NERVOUS SYSTEM; BLOOD CHOLESTEROL; DECISION-TREE ALGORITHM; GENOTYPES; HEART RATE VARIABILITY; MACHINE LEARNING CLASSIFICATION; MACHINE LEARNING METHODS; MANN-WHITNEY; NON-PARAMETRIC; RENIN-ANGIOTENSIN SYSTEM; TREE MACHINES; TYPE II;

BIOMEDICAL ENGINEERING; BLOOD PRESSURE; CLASSIFICATION (OF INFORMATION); DECISION TREES; HEART; LEARNING SYSTEMS; NORMAL DISTRIBUTION;

LEARNING ALGORITHMS;

EID: 84863684112     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.2316/P.2012.764-084     Document Type: Conference Paper

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