Use of random forest to estimate population attributable fractions from a case-control study of Salmonella enterica serotype Enteritidis infections

Epidemiology and Infection

Volumn 143, Issue 13, 2015, Pages 2786-2794

  Gu, W ^a   Vieira, A R ^a   Hoekstra, R M ^b   Griffin, P M ^a   Cole, D ^a  

^a CENTERS FOR DISEASE CONTROL AND PREVENTION   (United States)

^b NATIONAL CENTER FOR EMERGING AND ZOONOTIC INFECTIOUS DISEASES   (United States)

Author keywords

Causality; counterfactual; foodborne diseases; logistic regression; machine learning

Indexed keywords

ARTICLE; CASE CONTROL STUDY; CONTROLLED STUDY; DIARRHEA; ENVIRONMENTAL EXPOSURE; FEEDING BEHAVIOR; FOOD HANDLING; FOOD SAFETY; HUMAN; LOGISTIC REGRESSION ANALYSIS; MACHINE LEARNING; NONHUMAN; PREDICTION; PROBABILITY; PROPORTIONAL HAZARDS MODEL; RANDOM FOREST; RECEIVER OPERATING CHARACTERISTIC; SALMONELLA ENTERICA SEROVAR ENTERITIDIS; STRUCTURED QUESTIONNAIRE; TYPHOID FEVER; ANIMAL; DECISION TREE; EPIDEMIC; FOOD CONTROL; ISOLATION AND PURIFICATION; MICROBIOLOGY; PREDICTIVE VALUE; RISK FACTOR; SALMONELLA FOOD POISONING; SEROTYPE; STATISTICAL MODEL; UNITED STATES;

ANIMALS; CASE-CONTROL STUDIES; DECISION TREES; DISEASE OUTBREAKS; FOOD MICROBIOLOGY; HUMANS; LOGISTIC MODELS; PREDICTIVE VALUE OF TESTS; RISK FACTORS; SALMONELLA ENTERITIDIS; SALMONELLA FOOD POISONING; SEROGROUP; UNITED STATES;

EID: 84941024285     PISSN: 09502688     EISSN: 14694409     Source Type: Journal    
DOI: 10.1017/S095026881500014X     Document Type: Article

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