Background: Acute myocardial infarction (AMI) is one of the most common diagnoses in hospitalized patients. Increased plasma hemostatic markers were noted in acute myocardial infarction, indicating that the blood coagulation system is highly activated in those patients. Aims of the study: To study the level of intrinsic coagulation factors including (FVIII:C, FIX:C ,FXI:C ,FXII:C ) in patients with acute myocardial infarction. Type of the study: Cross –sectional study. Methods: Thirty patients (their age range is 48-68 years) were included in this study (9 female, 21 male) who were just admitted to the coronary care unit in AL-Yarmouk Teaching Hospital and diagnosed as having acute myocardial infarction patients, blood samples were tak

Background: This study aimed to determine the cephalometric values of tetragon analysis on a sample of Iraqi adults with normal occlusion. Material and methods: Forty digital true lateral cephalometric radiographs belong to 20 males and 20 females having normal dental relation were analyzed using AutoCAD program 2009. Descriptive statistics and sample comparison with Fastlicht norms were obtained. Results: The results showed that maxillary and mandibular incisors were more proclined and the maxillary/mandibular planes angle was lower in Iraqi sample than Caucasian sample. Conclusion: It's recommended to use result from this study when using tetragon analysis for Iraqis to get more accurate result.

The present study deals with the websites of Iraqi political parties on the internet to identify the effectiveness in providing communicative applications that help audience to participate, express their opinions, their positions, and other aspects reflecting the extent of employing modern technological tools to allow opportunities for political, and democratic participation since the internet has become an effective tool for political communications of political parties. The research sample includes eight political parties. The research concludes that the Iraqi political parties do not employ interactive communication patterns to reflect their interests in communicating with the public, providing opportunities for their participation an

Objective: To evaluate the therapeutic activity of probiotics mixture of Lactobacillus plantarum and Lactobacillus acidophilus towards Cryptosporidium infection in experimentally infected mice. Oocysts of Cryptosporidium were separated from the stool of humans to infect mice. Methods: Forty male albino mice were split equally into four groups, every group contained 10 mice, the group I (early treated group), were treated from the 1st day from infection to the 11th post-infection, group II (late treated group), were treated from the 4th day from infection to the 15th post-infection, and group (III) (untreated group), were mice considered as a positive control group. Results: It was showed that daily application of a mixture of L. plantarum w

Identifying breast cancer utilizing artificial intelligence technologies is valuable and has a great influence on the early detection of diseases. It also can save humanity by giving them a better chance to be treated in the earlier stages of cancer. During the last decade, deep neural networks (DNN) and machine learning (ML) systems have been widely used by almost every segment in medical centers due to their accurate identification and recognition of diseases, especially when trained using many datasets/samples. in this paper, a proposed two hidden layers DNN with a reduction in the number of additions and multiplications in each neuron. The number of bits and binary points of inputs and weights can be changed using the mask configuration

<p>Currently, breast cancer is one of the most common cancers and a main reason of women death worldwide particularly in<strong> </strong>developing countries such as Iraq. our work aims to predict the type of tumor whether benign or malignant through models that were built using logistic regression and neural networks and we hope it will help doctors in detecting the type of breast tumor. Four models were set using binary logistic regression and two different types of artificial neural networks namely multilayer perceptron MLP and radial basis function RBF. Evaluation of validated and trained models was done using several performance metrics like accuracy, sensitivity, specificity, and AUC (area under receiver ope