Exploring metabolic syndrome serum profiling based on gas chromatography mass spectrometry and random forest models

Analytica Chimica Acta

Volumn 827, Issue , 2014, Pages 22-27

  Lin, Zhang ^a   Vicente Gonçalves, Carlos M ^a,b   Dai, Ling ^a   Lu, Hong mei ^a   Huang, Jian hua ^a   Ji, Hongchao ^a   Wang, Dong sheng ^c   Yi, Lun zhao ^a   Liang, Yi zeng ^a  

^a CENTRAL SOUTH UNIVERSITY   (China)

^b UNIVERSITY OF CÁDIZ   (Spain)

^c CENTRAL SOUTH UNIVERSITY   (China)

Author keywords

Biomarker; GC MS; Metabolic syndrome; Random forest; Serum profiling

Indexed keywords

BIOMARKERS; BIOMOLECULES; BLOOD PRESSURE; BODY FLUIDS; GAS CHROMATOGRAPHY; METABOLISM; METABOLITES;

GAS CHROMATOGRAPHY-MASS SPECTROMETRY; GC-MS; HIGH BLOOD PRESSURES; METABOLIC PROFILES; METABOLIC SYNDROMES; RANDOM FORESTS; SERUM PROFILING; VARIABLE IMPORTANCES;

DECISION TREES;

2 HYDROXYBUTYRIC ACID; BIOLOGICAL MARKER; GLUCOSE; HYDROXYBUTYRIC ACID; INOSITOL; UNCLASSIFIED DRUG;

ADULT; AGED; ARTICLE; BLOOD ANALYSIS; BLOOD SAMPLING; CONTROLLED STUDY; DIAGNOSTIC VALUE; EXPLORATORY RESEARCH; FEMALE; HUMAN; INVERSE GAS CHROMATOGRAPHY; MACHINE LEARNING; MAJOR CLINICAL STUDY; MALE; METABOLIC SYNDROME X; METABOLOMICS; PRIORITY JOURNAL; RANDOM FOREST MODEL;

EID: 84900426313     PISSN: 00032670     EISSN: 18734324     Source Type: Journal    
DOI: 10.1016/j.aca.2014.04.008     Document Type: Article

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