First Trimester Noninvasive Prenatal Diagnosis: A Computational Intelligence Approach

IEEE J Biomed Health Inform. 2016 Sep;20(5):1427-38. doi: 10.1109/JBHI.2015.2462744. Epub 2015 Jul 29.

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.

MeSH terms

  • Artificial Intelligence*
  • Biomarkers / blood
  • Chromosome Disorders / diagnosis*
  • Computational Biology / methods*
  • Crown-Rump Length
  • Female
  • Humans
  • Maternal Age
  • Pregnancy
  • Pregnancy Trimester, First*
  • Prenatal Diagnosis / methods*

Substances

  • Biomarkers