Non-invasive diagnosis of risk in dengue patients using bioelectrical impedance analysis and artificial neural network

Medical and Biological Engineering and Computing

Volumn 48, Issue 11, 2010, Pages 1141-1148

  Ibrahim, F ^a   Faisal, T ^a   Mohamad Salim, M I ^a   Taib, M N ^b  

^a UNIVERSITY OF MALAYA   (Malaysia)

^b UNIVERSITI TEKNOLOGI MARA   (Malaysia)

Author keywords

Artificial neural network; Bioelectrical impedance analysis; Classify; Dengue fever; Risk; Severity

Indexed keywords

ARTIFICIAL NEURAL NETWORK; BIOELECTRICAL IMPEDANCE ANALYSIS; CLASSIFY; DENGUE FEVER; SEVERITY;

AMINO ACIDS; BENCHMARKING; BLOOD; ELECTRIC IMPEDANCE;

NEURAL NETWORKS;

DIAGNOSTIC AGENT;

ALGORITHM; ARTICLE; ARTIFICIAL NEURAL NETWORK; COMPUTER ASSISTED DIAGNOSIS; DENGUE; EARLY DIAGNOSIS; FEMALE; HUMAN; IMPEDANCE; MALE; METHODOLOGY; RISK ASSESSMENT;

ALGORITHMS; DENGUE; DIAGNOSIS, COMPUTER-ASSISTED; EARLY DIAGNOSIS; ELECTRIC IMPEDANCE; FEMALE; HUMANS; MALE; NEURAL NETWORKS (COMPUTER); RISK ASSESSMENT;

EID: 78649322287     PISSN: 01400118     EISSN: None     Source Type: Journal    
DOI: 10.1007/s11517-010-0669-z     Document Type: Article

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