Predicting the serum digoxin concentrations of infants in the neonatal intensive care unit through an artificial neural network

Background Given its narrow therapeutic range, digoxin’s pharmacokinetic parameters in infants are difficult to predict due to variation in birth weight and gestational age, especially for critically ill newborns. There is limited evidence to support the safety and dosage requirements of digoxin, le...

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Veröffentlicht in:	BMC pediatrics Jg. 19; H. 1; S. 517 - 11
Hauptverfasser:	Yao, Shu-Hui, Tsai, Hsiang-Te, Lin, Wen-Lin, Chen, Yu-Chieh, Chou, Chiahung, Lin, Hsiang-Wen
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	London BioMed Central 27.12.2019 BioMed Central Ltd Springer Nature B.V BMC
Schlagworte:	Age Algorithms Artificial neural network Artificial neural networks Cardiotonic agents Clinical medicine Congenital diseases Congenital heart defects Coronary vessels Critical care Datasets Digoxin Digoxin concentration Drug dosages Gender General pediatric medicine and surgery Health aspects Heart failure Hospitals Infants Intensive care Internal Medicine Medicine Medicine & Public Health Neonatal care Neonatal intensive care Neural networks Newborn babies Newborn infants Nonsteroidal anti-inflammatory drugs Patent ductus arteriosus Pediatrics Regression analysis Research Article Safety regulations Therapeutic drug monitoring Variables Taiwan Digoxin concentration Infants Artificial neural network Patent ductus arteriosus
ISSN:	1471-2431, 1471-2431
Online-Zugang:	Volltext
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