title: First Trimester Noninvasive Prenatal Diagnosis: A Computational Intelligence Approach.
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 database(1) (1)The dataset can become available for academic purposes by communicating directly with the authors.
authors.forename: Andreas C
authors.initials: AC
authors.lastname: Neocleous
authors.forename: Kypros H
authors.initials: KH
authors.lastname: Nicolaides
authors.forename: Christos N
authors.initials: CN
authors.lastname: Schizas
mesh_terms: D001185:Artificial Intelligence; D015415:Biomarkers / Q000097:blood; D025063:Chromosome Disorders / Q000175:diagnosis*; D019295:Computational Biology / Q000379:methods*; D018568:Crown-Rump Length; D005260:Female; D006801:Humans; D008423:Maternal Age; D011247:Pregnancy; D011261:Pregnancy Trimester, First; D011296:Prenatal Diagnosis / Q000379:methods*
chemical_list: D015415:Biomarkers