First Trimester Noninvasive Prenatal Diagnosis: A Computational Intelligence Approach

Neocleous, Andreas C.; Nicolaides, Kypros H.; Schizas, Christos N.

doi:10.1109/JBHI.2015.2462744

dc.contributor.author	Neocleous, Andreas C.	en
dc.contributor.author	Nicolaides, Kypros H.	en
dc.contributor.author	Schizas, Christos N.	en
dc.creator	Neocleous, Andreas C.	en
dc.creator	Nicolaides, Kypros H.	en
dc.creator	Schizas, Christos N.	en
dc.date.accessioned	2019-11-13T10:41:23Z
dc.date.available	2019-11-13T10:41:23Z
dc.date.issued	2016
dc.identifier.issn	2168-2194
dc.identifier.uri	http://gnosis.library.ucy.ac.cy/handle/7/54577
dc.description.abstract	The objective of this study is to examine the potential value of using machine learning techniques such as artificial neural network (ANN) schemes for the noninvasive estimation, at 11-13 weeks of gestation, the risk for euploidy, trisomy 21 (T21), and other chromosomal aneuploidies (O.C.A.), from suitable sonographic, biochemical markers, and other relevant data. A database1 1The dataset can become available for academic purposes by communicating directly with the authors. © 2013 IEEE.	en
dc.source	IEEE Journal of Biomedical and Health Informatics	en
dc.source.uri	https://www.scopus.com/inward/record.uri?eid=2-s2.0-84987703592&doi=10.1109%2fJBHI.2015.2462744&partnerID=40&md5=e15ddcd3d85193b01f18645fbe710829
dc.subject	Risk perception	en
dc.subject	mathematical model	en
dc.subject	Artificial intelligence	en
dc.subject	Neural networks	en
dc.subject	human	en
dc.subject	algorithm	en
dc.subject	Chromosomes	en
dc.subject	Diagnosis	en
dc.subject	Article	en
dc.subject	chorionic gonadotropin beta subunit	en
dc.subject	aneuploidy	en
dc.subject	echography	en
dc.subject	false positive result	en
dc.subject	first trimester pregnancy	en
dc.subject	artificial neural network	en
dc.subject	mathematical parameters	en
dc.subject	Bioinformatics	en
dc.subject	Biochemistry	en
dc.subject	Prenatal diagnosis	en
dc.subject	DNA methylation	en
dc.subject	support vector machine	en
dc.subject	machine learning	en
dc.subject	Learning systems	en
dc.subject	trisomy 21	en
dc.subject	Machine learning techniques	en
dc.subject	Biochemical markers	en
dc.subject	chromosomal abnormalities	en
dc.subject	computational	en
dc.subject	false negative result	en
dc.subject	First trimesters	en
dc.subject	intelligence	en
dc.subject	k nearest neighbor	en
dc.subject	non invasive procedure	en
dc.subject	non-invasive prenatal diagnosis	en
dc.subject	Noninvasive estimation	en
dc.subject	pregnancy associated plasma protein A	en
dc.title	First Trimester Noninvasive Prenatal Diagnosis: A Computational Intelligence Approach	en
dc.type	info:eu-repo/semantics/article
dc.identifier.doi	10.1109/JBHI.2015.2462744
dc.description.volume	20
dc.description.issue	5
dc.description.startingpage	1427
dc.description.endingpage	1438
dc.author.faculty	002 Σχολή Θετικών και Εφαρμοσμένων Επιστημών / Faculty of Pure and Applied Sciences
dc.author.department	Τμήμα Πληροφορικής / Department of Computer Science
dc.type.uhtype	Article	en
dc.description.notes	<p>Cited By :1</p>	en
dc.source.abbreviation	IEEE J.Biomedical Health Informat.	en
dc.contributor.orcid	Schizas, Christos N. [0000-0001-6548-4980]
dc.gnosis.orcid	0000-0001-6548-4980

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