A Data-Driven Algorithm Integrating Clinical and Laboratory Features for the Diagnosis and Prognosis of Necrotizing Enterocolitis

Necrotizing enterocolitis (NEC) is a major source of neonatal morbidity and mortality. Since there is no specific diagnostic test or risk of progression model available for NEC, the diagnosis and outcome prediction of NEC is made on clinical grounds. The objective in this study was to develop and va...

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Veröffentlicht in:	PloS one Jg. 9; H. 2; S. e89860
Hauptverfasser:	Ji, Jun, Ling, Xuefeng B., Zhao, Yingzhen, Hu, Zhongkai, Zheng, Xiaolin, Xu, Zhening, Wen, Qiaojun, Kastenberg, Zachary J., Li, Ping, Abdullah, Fizan, Brandt, Mary L., Ehrenkranz, Richard A., Harris, Mary Catherine, Lee, Timothy C., Simpson, B. Joyce, Bowers, Corinna, Moss, R. Lawrence, Sylvester, Karl G.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States Public Library of Science 28.02.2014 Public Library of Science (PLoS)
Schlagworte:	Algorithms Biology Birth weight Colleges & universities Computer science Consortia Data processing Development and progression Diagnosis Diagnostic systems Discriminant analysis Disease Enterocolitis Enterocolitis, Necrotizing - diagnosis Enterocolitis, Necrotizing - pathology Epidemiology Female Gangrene Gastrointestinal diseases Health aspects Health risks Hospitals Humans Infant, Newborn Infants Laboratories Learning algorithms Machine learning Male Medical diagnosis Medical prognosis Medicine Morbidity Mortality Necrosis Necrotizing enterocolitis Neonates Newborn babies Pediatrics Process controls Prognosis Risk Smartphones Surgery Training Urine Ohio California United States > US Texas China
ISSN:	1932-6203, 1932-6203
Online-Zugang:	Volltext
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