The New Methods for the Prenatal Diagnosis of Down syndrome

The aim of the present research is to determine the appropriate diagnostic methods to find out the affected fetuses with Down Syndrome in order to decrease as possible subjecting the pregnant women to invasive prenatal diagnosis . This is a Prospective – practical study, where /1137/ pregnant women at 13- 16 gestation weeks, ( age range: 20-42 years) were included. Biochemical screening of the pregnant women, ultrasound screening of the fetuses: nuchal translucency, nasal bone, which helped us to isolate the highrisk pregnancies for Down syndrome (the potential rate of incidence ≥ 0.4%). The screen positive group included 57 pregnant ( 5.01% ) . Amniocentesis and subsequently karyotyping was done to each woman in this group . We found out 4 affected fetuses from 5 ( 80%) , because the following up of the remaining pregnancies revealed a fifth affected newborn with Down syndrome. The early prenatal diagnosis of Down syndrome was possible in ( 80% ) by subjecting only ( 5.01% ) of pregnants to the invasive prenatal diagnosis .

The Level of the Special Needs of Parents of Children with Down Syndrome in the Light of some of The Variables (A field study in the province of Damascus)

The research aims to identify the level of the special needs of parents of children with Down Syndrome in the province of Damascus, and the knowledge of the differences in the level oftheir needs, according to the variables (sex, educational level, monthly income).

Teaching expression Of happiness and sadness

With the increase in social networks, people have started to share information via different types of social media. Among themwere sites for exchanging people's opinions and others to exchange stories about real life and stories for children. In this work we made use of children's stories and employed them to teach children with Down syndrome the correct feelings by reading a story for them, converting it into text, processing the text using natural languages and extracting feelings automatically from This story, and to achieve this, we used several techniques, combined them, and compared their results on a number of short stories dedicated to children, where each of the different techniques that were unsupervised, such as Dictionary Based or supervised, such as data-dependent neural networks, were used to analyze feelings, where we used multiple classifiers. They are Support Vector Machine, Stochastic Gradient Descent, Decision Tree, Random Forest, Naïve Bayes, K-Nearest Neighbor, and Nearest Centroid We also used deep neural networks as the example of RNN. Finally, the correct sentiment for the story was reached through Dictionary Based which gave the best accuracy and then showed a photo that shows the child the expression they want to start with The events of this story to interact with him and learn the correct expression