TV drama has gone through many developmental stages until it reached and settled in the form of TV series of thirty episodes. Alongside the development of the TV technologies and the widespread of satellite channels, the form of the TV drama has changed and the series has consisted of two parts and then parts multiplied until they amounted to ten parts and more. This form of TV drama has become an artistic phenomenon, that once the series is displayed on one of the channels and achieves a noticeable success, its producers work to produce a second part of that series and so on. This form of TV drama has remained away from being researched.
This has urged the researcher to accomplish this study entitled (TV series of multiple parts fro

This study was designed to compare the effect of two types of viral hepatitis A and E (HAV
and HEV) on liver functions in Iraqi individuals by the measurement of biochemical changes
associated with hepatitis.
The study performed on 58 HEV and 66 HAV infected patients compared with 28 healthy
subjects. The measured biochemical tests include total serum bilirubin, serum transminases (ALT
and AST) alkaline phosphatase (ALP) and gamma glutamyl transferase (GGT).
The study showed that adolescent and young adults (17-29) years, were mostly affected by
HEV while children (5-12) years were frequently affected by HAV. The severity of liver damage in
HEV patients was higher than HAV patients as a result of high serum transa

KE Sharquie, HA Hassan, AA Noaimi, IRAQI JOURNAL OF COMMUNITY MEDICINE, 2010

Background: Although various imaging modalities are available for evaluating suspicious breast lesions, ultrasound-based Shear-Wave Elastography (SWE) is an advanced, non-invasive technique complementary to grayscale sonography. This technique evaluates the elasticity of a specific tissue by applying sonic pressure to that tissue.

Objective: The aim is to assess the role of SWE in evaluating solid breast masses in correlation to histopathological study results.

Subjects and Methods: This prospective study was done in a tertiary care teaching hospital from September 2019 to August 2020. A study population of 50 women aged 18 years or above with an

Background: Blastocystis spp. distributes world widely and the genus Blastocystis include many subtypes that are isolated from human intestinal tract. It is considered the most common parasite detected in human being.

Objectives: To evaluate the incidence of Blastocystis spp. among leukemic children, to find out its association with the presence of symptoms (diarrhea and abdominal pain), and to assess the efficacy of different staining methods in detection of Blastocystis spp. 

Type of the study: cross-sectional study.

Method: 103 children were enrolled in this study, 53 leukemic patients and 50 healthy con

Background: Treatment of invasive prolactinoma, which has several characteristics including invasive growth into cavernous sinuses and formation of giant adenomas compressing adjacent neural structures, resulting in neurological dysfunction, has been very challenging. There are relatively few reports available describing long-term treatment outcome.

Aims of the study: In this study we evaluate the results of cabergoline administration as initial treatment during 4 years follow up period.

Methods: We prospectively categorized 36 patients into four groups according to the results of 3 months of cabergoline treatment: group 1, tumor volume reduction (TVR) ˃25% with normaliz

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class