Identification and classification of high risk groups for Coal Workers' Pneumoconiosis using an artificial neural network based on occupational histories: A retrospective cohort study

BMC Public Health

Volumn 9, Issue , 2009, Pages

  Liu, Hongbo ^a   Tang, Zhifeng ^a   Yang, Yongli ^b   Weng, Dong ^a   Sun, Gao ^a   Duan, Zhiwen ^a   Chen, Jie ^a  

^a CHINA MEDICAL UNIVERSITY   (China)

^b General Hospital of Tiefa Coal Corporation   (China)

Author keywords

[No Author keywords available]

Indexed keywords

ADULT; ARTICLE; ARTIFICIAL NEURAL NETWORK; CHINA; COAL WORKER; DEVELOPING COUNTRY; DUST EXPOSURE; HIGH RISK POPULATION; HUMAN; MEDICAL RECORD; OCCUPATIONAL HAZARD; PATIENT IDENTIFICATION; PNEUMOCONIOSIS; RECEIVER OPERATING CHARACTERISTIC; RETROSPECTIVE STUDY; RISK FACTOR; SENSITIVITY ANALYSIS; SENSITIVITY AND SPECIFICITY; COAL MINING; COHORT ANALYSIS; DUST; EMPLOYMENT; FOLLOW UP; LUNG FIBROSIS; MIDDLE AGED; OCCUPATIONAL EXPOSURE; PREVALENCE; RADIOGRAPHY; RETIREMENT; STATISTICAL MODEL; UNITED STATES;

COAL MINING; COHORT STUDIES; DUST; EMPLOYMENT; FOLLOW-UP STUDIES; HUMANS; LOGISTIC MODELS; MIDDLE AGED; OCCUPATIONAL EXPOSURE; PNEUMOCONIOSIS; PREVALENCE; PULMONARY FIBROSIS; RETIREMENT; RISK FACTORS; UNITED STATES;

EID: 70350011936     PISSN: None     EISSN: 14712458     Source Type: Journal    
DOI: 10.1186/1471-2458-9-366     Document Type: Article

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