First Trimester Noninvasive Prenatal Diagnosis: A Computational Intelligence Approach

Andreas Neocleous, K. H. Nicolaides, Christos N. Schizas

IEEE Journal of Biomedical and Health Informatics · 2015 · 34 citations · 26 references

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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.

References

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