An efficient machine learning approach for diagnosis of paraquat-poisoned patients

Computers in Biology and Medicine

Volumn 59, Issue , 2015, Pages 116-124

  Hu, Lufeng ^a   Hong, Guangliang ^a   Ma, Jianshe ^b   Wang, Xianqin ^b   Chen, Huiling ^c  

^a THE FIRST AFFILIATED HOSPITAL OF WENZHOU MEDICAL UNIVERSITY   (China)

^b WENZHOU MEDICAL UNIVERSITY   (China)

^c WENZHOU UNIVERSITY   (China)

Author keywords

Extreme learning machine; Medical diagnosis; Paraquat; Poison

Indexed keywords

ARTIFICIAL INTELLIGENCE; BLOOD; GAS CHROMATOGRAPHY; HERBICIDES; KNOWLEDGE ACQUISITION; LEARNING ALGORITHMS; LEARNING SYSTEMS; MASS SPECTROMETRY;

CLASSIFICATION TECHNIQUE; EXTREME LEARNING MACHINE; MACHINE LEARNING APPROACHES; MACHINE LEARNING TECHNIQUES; PARAQUAT; POISON; RECEIVER OPERATING CHARACTERISTIC CURVES; SENSITIVITY AND SPECIFICITY;

DIAGNOSIS;

ALANINE; ARABINITOL; BUTYRIC ACID; GLUTAMINE; GLYCEROPHOSPHATE; HERBICIDE; INOSITOL; LEUCINE; LINOLEIC ACID; PARAQUAT; PHENYLALANINE; PIPERAZINE; PROLINE; PURINE; SORBITOL; THREONINE; TYROSINE; URIC ACID; VALINE; XYLITOL;

ADULT; ARTICLE; BLOOD SAMPLING; CLASSIFICATION; CLINICAL ARTICLE; CLINICAL TRIAL (TOPIC); CONTROLLED STUDY; DIAGNOSTIC ACCURACY; DIAGNOSTIC TEST ACCURACY STUDY; EXTREME LEARNING MACHINE; FEMALE; GAS CHROMATOGRAPHY; HUMAN; MACHINE LEARNING; MALE; MASS SPECTROMETRY; METABOLITE; MODEL; PARAQUAT POISONING; PRIORITY JOURNAL; RECEIVER OPERATING CHARACTERISTIC; SENSITIVITY AND SPECIFICITY; ADOLESCENT; COMPUTER ASSISTED DIAGNOSIS; DIAGNOSIS; INTOXICATION; MIDDLE AGED; PROCEDURES; YOUNG ADULT;

ADOLESCENT; ADULT; DIAGNOSIS, COMPUTER-ASSISTED; FEMALE; HUMANS; MACHINE LEARNING; MALE; MIDDLE AGED; PARAQUAT; POISONING; ROC CURVE; YOUNG ADULT;

EID: 84923046261     PISSN: 00104825     EISSN: 18790534     Source Type: Journal    
DOI: 10.1016/j.compbiomed.2015.02.003     Document Type: Article

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