Predicting length-of-stay in preterm neonates

European Journal of Pediatrics

Volumn 158, Issue 1, 1999, Pages 59-62

  Zernikow, B ^a   Holtmannspotter K ^a   Michel, E ^b   Hornschuh, F ^a   Groote, K ^a   Hennecke, K H ^a  

^a UNIVERSITY OF WITTEN HERDECKE   (Germany)

^b Medizinischer Dienst   (Germany)

Author keywords

Artificial neural network; Length of stay; Neural networks computer; Prediction; Preterm neonate

Indexed keywords

ARTICLE; ARTIFICIAL NEURAL NETWORK; HUMAN; LENGTH OF STAY; MAJOR CLINICAL STUDY; MEDICAL DECISION MAKING; NEWBORN; PREMATURITY; PRIORITY JOURNAL; PROGNOSIS; RISK ASSESSMENT;

HUMANS; INFANT, NEWBORN; INFANT, PREMATURE; INFANT, PREMATURE, DISEASES; LENGTH OF STAY; LINEAR MODELS; NEURAL NETWORKS (COMPUTER); PROGNOSIS; RETROSPECTIVE STUDIES;

EID: 0033002639     PISSN: 03406199     EISSN: None     Source Type: Journal    
DOI: 10.1007/s004310051010     Document Type: Article

References (8)

1. Altman DG (1991) Practical statistics for medical research. Chapman & Hall, London
2. De Courcy-Wheeler RHB, Wolfe CDA, Fitzgerald A, Spencer M, Goodmann JDS, Gamsu HR (1995) Use of the CRIB (clinical risk index for babies) score in prediction of neonatal mortality and morbidity. Arch Dis Child 73:F32-F36
3. Escobar GJ, Fischer A, Li DK, Kremers R, Armstrong MA (1995) Score for neonatal acute physiology: validation in three Kaiser permanent neonatal intensive care units. Pediatrics 96:918-922
4. Hertz J, Krogh A, Palmer R (1991) Introduction to the theory of neural computation. Addison Wesley, Reading
5. Jacobs RA (1988) Increased rates of convergence through learning rate adaptation. Neural Networks 4:295-308
6. Powell P, Powell C, Hollis S, Robinson M (1992) When will my baby go home? Arch Dis Child 67:1214-1216
7. Predict Manual (1995) NeuralWare, Pittsburgh
8. Ryan S, Sics A, Congdon P (1988) Cost of neonatal care. Arch Dis Child 63:303-306