An optimal tumor marker group-coupled artificial neural network for diagnosis of lung cancer

Expert Systems with Applications

Volumn 38, Issue 9, 2011, Pages 11329-11334

  Wu, Yongjun ^a,d   Wu, Yiming ^b   Wang, Jing ^b   Yan, Zhen ^a   Qu, Lingbo ^a   Xiang, Bingren ^c   Zhang, Yiguo ^d,e  

^a ZHENGZHOU UNIVERSITY   (China)

^b THE FIRST AFFILIATED HOSPITAL OF ZHENGZHOU UNIVERSITY   (China)

^c CHINA PHARMACEUTICAL UNIVERSITY   (China)

^d UNIVERSITY OF DUNDEE   (United Kingdom)

^e CHONGQING UNIVERSITY   (China)

Author keywords

Artificial neural network; Diagnosis; Lung cancer; Tumor marker

Indexed keywords

ARTIFICIAL NEURAL NETWORK; CANCER DIAGNOSIS; CANCER PATIENTS; CARCINOEMBRYONIC ANTIGEN; DEATH RATES; DIAGNOSIS OF LUNG CANCER; DIAGNOSIS TOOLS; EVALUATION MODELS; EXPERIMENTAL PROCEDURE; INTELLIGENT DIAGNOSIS SYSTEM; INTERLEUKIN-6; LUNG CANCER; LUNG DISEASE; MULTIPLE LOGISTIC REGRESSION; NEURON SPECIFIC ENOLASE; NORMAL CONTROLS; PSEUDOURIDINE; SENSITIVITY AND SPECIFICITY; SIALIC ACIDS; SURVIVAL RATE; TUMOR MARKER; TUMOR MARKERS;

ANTIGENS; BIOLOGICAL ORGANS; CARBOXYLIC ACIDS; DISEASE CONTROL; DISEASES; METAL IONS; NEURAL NETWORKS; NITRIC ACID; NITRIC OXIDE; OPTIMIZATION; POPULATION STATISTICS; REGRESSION ANALYSIS; TUMORS;

DIAGNOSIS;

EID: 79955591509     PISSN: 09574174     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.eswa.2011.02.183     Document Type: Article

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