Predicting congenital heart defects: A comparison of three data mining methods

PLoS ONE

Volumn 12, Issue 5, 2017, Pages

  Luo, Yanhong ^a   Li, Zhi ^a   Guo, Husheng ^b   Cao, Hongyan ^a   Song, Chunying ^c   Guo, Xingping ^c   Zhang, Yanbo ^a  

^a SHANXI MEDICAL UNIVERSITY   (China)

^b SHANXI UNIVERSITY   (China)

^c Shanxi Population and Family Planning Science Research Institute   (China)

Author keywords

[No Author keywords available]

Indexed keywords

ADULT; AREA UNDER THE CURVE; ARTICLE; CHINA; CONGENITAL HEART MALFORMATION; CONGENITAL MALFORMATION; CONTROLLED STUDY; CROSS-SECTIONAL STUDY; DATA MINING; DRUG USE; ENVIRONMENTAL FACTOR; EPIDEMIOLOGICAL DATA; FAMILY HISTORY; FEMALE; FOLIC ACID DEFICIENCY; HUMAN; INCOME; INTERMETHOD COMPARISON; LIFESTYLE; LIVE BIRTH; MATERNAL AGE; MEASUREMENT; MEASUREMENT ACCURACY; NUTRITION; POPULATION RESEARCH; POPULATION RISK; PREDICTION; PREGNANCY; RANDOM FOREST; RETROSPECTIVE STUDY; RISK FACTOR; SUPPORT VECTOR MACHINE; TRUE NEGATIVE RATE; TRUE POSITIVE RATE; WEIGHTED RANDOM FOREST; WEIGHTED SUPPORT VECTOR MACHINE; ALGORITHM; COMPARATIVE STUDY; HEART DEFECTS, CONGENITAL; NEWBORN; PROCEDURES;

ADULT; ALGORITHMS; CHINA; CROSS-SECTIONAL STUDIES; DATA MINING; FEMALE; HEART DEFECTS, CONGENITAL; HUMANS; INFANT, NEWBORN; PREGNANCY; RETROSPECTIVE STUDIES; RISK FACTORS; SUPPORT VECTOR MACHINE;

EID: 85019714517     PISSN: None     EISSN: 19326203     Source Type: Journal    
DOI: 10.1371/journal.pone.0177811     Document Type: Article

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