Predicting congenital heart defects: A comparison of three data mining methods
PloS one, 2017-05, Vol.12 (5), p.e0177811-e0177811 [Peer Reviewed Journal]COPYRIGHT 2017 Public Library of Science ;COPYRIGHT 2017 Public Library of Science ;2017 Luo et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;2017 Luo et al 2017 Luo et al ;ISSN: 1932-6203 ;EISSN: 1932-6203 ;DOI: 10.1371/journal.pone.0177811 ;PMID: 28542318
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