Zobrazeno 1 - 10
of 12
pro vyhledávání: '"Shing-yan Lee"'
Publikováno v:
Journal of Pediatric Surgery Case Reports, Vol 3, Iss 9, Pp 364-366 (2015)
Foreign bodies are extremely rare in preterm neonates. The majority are iatrogenic. We describe a neonate of 27 weeks gestation who was found to have an 18 mm long suction catheter at the right main bronchi after resuscitation in another hospital. It
Externí odkaz:
https://doaj.org/article/616ea589187648cab2f4d6ef88bddeb3
Publikováno v:
Journal of Pediatric Surgery Case Reports, Vol 3, Iss 9, Pp 364-366 (2015)
Foreign bodies are extremely rare in preterm neonates. The majority are iatrogenic. We describe a neonate of 27 weeks gestation who was found to have an 18 mm long suction catheter at the right main bronchi after resuscitation in another hospital. It
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::eb73b2429ab3d1e3f850aec73cb6bbcd
http://www.sciencedirect.com/science/article/pii/S2213576615000913
http://www.sciencedirect.com/science/article/pii/S2213576615000913
Autor:
Man Chun Chiu, Chun-tat Kong, Wai-yau Mak, Yiu-Keung Shiu, Nai-chung Fong, Shing-yan Lee, Chun Bong Chow
Publikováno v:
Chinese Medical Journal. 119:1485-1488
A baby girl was born at 41 weeks and 2 days of gestation by vaginal delivery with birth weight of 2.68 kg. The perinatal history was unremarkable and she was the first baby of a family without history of congenital heart disease. Routine neonatal scr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6120cb491227443ed3088c87ec35cadc
https://doi.org/10.1097/00029330-200609010-00015
https://doi.org/10.1097/00029330-200609010-00015
Publikováno v:
Decision Support Systems. 38:451-472
This paper describes a novel data mining algorithm that employs cooperative coevolution and a hybrid approach to discover Bayesian networks from data. A Bayesian network is a graphical knowledge representation tool. However, learning Bayesian network
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::916838c67dafb7d7e9fec8e58c24ddd1
https://doi.org/10.1016/s0167-9236(03)00115-5
https://doi.org/10.1016/s0167-9236(03)00115-5
Publikováno v:
Annals of the Academy of Medicine, Singapore. 35:582-584
Introduction: Sarcosinaemia is a rare metabolic disorder which has not been reported in Asia. Clinical Picture: The urine samples of 2 patients were screened as a routine metabolic screening offered for patients with mental retardation in our hospita
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::67da3ad3e445764b84383e6bad1a43c3
https://doi.org/10.47102/annals-acadmedsg.v35n8p582
https://doi.org/10.47102/annals-acadmedsg.v35n8p582
Publikováno v:
Advanced Information and Knowledge Processing ISBN: 9781852338671
Bayesian networks are formal knowledge representation tools that provide reasoning under uncertainty. The applications of Bayesian networks are widespread, including data mining, information retrieval, and various diagnostic systems. Although Bayesia
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4781df7de1baa22b4d68a50b3750e1b4
https://doi.org/10.1007/1-84628-183-0_6
https://doi.org/10.1007/1-84628-183-0_6
Publikováno v:
ICDM
Describes a data mining approach that employs evolutionary programming to discover knowledge represented in Bayesian networks. There are two different approaches to the network learning problem. The first one uses dependency analysis, while the secon
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::bdfc0e1d3d5674436a237236c56d8fa1
https://doi.org/10.1109/icdm.2002.1183994
https://doi.org/10.1109/icdm.2002.1183994
Publikováno v:
Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600).
A novel hybrid framework is reported that improves upon our previous work, MDLEP, which uses evolutionary programming to solve the difficult Bayesian network learning problem. A new merge operator is also introduced that further enhances the efficien
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b2aced412909d34fa6371707b0b02e49
https://doi.org/10.1109/cec.2002.1004433
https://doi.org/10.1109/cec.2002.1004433
Autor:
Jain, Lakhmi C., Xindong Wu, Pal, Nikhil R., Jain, Lakhmi, Man Leung Wong, Shing Yan Lee, Kwong Sak Leung
Publikováno v:
Advanced Techniques in Knowledge Discovery & Data Mining; 2005, p153-175, 23p
Publikováno v:
Proceedings of the 2002 Congress on Evolutionary Computation, CEC'02 (Cat. No.02TH8600); 2002, p1314-1319, 6p