A machine learning technology to improve the risk of non-invasive prenatal tests.

Background: Timely and accurate diagnosis of genetic diseases can lead to proper action and prevention of irreparable events.

Objective: In this work we propose an integrated genetic-neural network (GNN) to improve the prediction risk of trisomy diseases including Down's syndrome (T21), Edwards' syndrome (T18) and Patau's Syndrome (T13).

Methods: A dataset including 561 pregnant were created.