Background: It is still difficult to give a final diagnosis in chronic myeloproliferative disorders (CMPDs) because of the overlap of the common pathological and clinical features of these disorders like bone marrow fibrosis which is considered important because it affects the normal function of the bone marrow. The collagen fibers are of different types, but in the bone marrow, the two main types are: collagen I, which is the most abundant type and collagen III (reticular) which is often associated with type I.
Objectives:To study bone marrow fibrosis (BMF) in samples of bone marrow biopsies (BMB) of chronic myeloid leukemia (CML) and other chronic myeloproliferative disorders using histochemical stains to establish the grade of fibr

Background: Laparoscopic cholecystectomy has many difficulties which include port Insertion, Dissectionof the Calot’s Triangle , Grasping of the Gallbladder , Wall thickness, Adhesion and extraction of theGallbladder. Aim of the Study: To predict how difficult cholecystectomy will be from assessing the patientpreoperatively which, in turn, help in decreasing the risks on the patients and preventing post-operativecomplications. Patients and Methods: A prospective study conducted in the department of General Surgeryat Al-Ramadi Teaching Hospital for the period of nine months from 15th of May 2018 till the 15th of February2019. It included 60 patients, all of them were undergone laparoscopic cholecystectomy for Gallstone. Patientswit

Asmari is the main productive reservoir in Abu Ghirab oilfield in the south-east part of Iraq. It has history production extends from 1976 up to now with several close periods. Recently, the reservoir suffers some problems in production, which are abstracted as water production rising with oil production declining in most wells. The water problem type of the field and wells is identified by using Chan's diagnostic plots (water oil ratio (WOR) and derivative water oil ratio (WOR') against time). The analytical results show that water problem is caused by the channeling due to high permeability zones, high water saturation zones, and faults or fracturing. The numerical approach is also used to study the water movement inside the reser

       In the current worldwide health crisis produced by coronavirus disease (COVID-19), researchers and medical specialists began looking for new ways to tackle the epidemic. According to recent studies, Machine Learning (ML) has been effectively deployed in the health sector. Medical imaging sources (radiography and computed tomography) have aided in the development of artificial intelligence(AI) strategies to tackle the coronavirus outbreak. As a result, a classical machine learning approach for coronavirus detection from      Computerized Tomography (CT) images was developed. In this study, the convolutional neural network (CNN) model for feature extraction and support vector machine (SVM) for the classification of axial

Asmari is the main productive reservoir in Abu Ghirab oilfield in the south-east part of Iraq. It has history production extends from 1976 up to now with several close periods. Recently, the reservoir suffers some problems in production, which are abstracted as water production rising with oil production declining in most wells. The water problem type of the field and wells is identified by using Chan's diagnostic plots (water oil ratio (WOR) and derivative water oil ratio (WOR') against time). The analytical results show that water problem is caused by the channeling due to high permeability zones, high water saturation zones, and faults or fracturing. The numerical approach is also used to study the water movement insi

Software-defined networking (SDN) presents novel security and privacy risks, including distributed denial-of-service (DDoS) attacks. In response to these threats, machine learning (ML) and deep learning (DL) have emerged as effective approaches for quickly identifying and mitigating anomalies. To this end, this research employs various classification methods, including support vector machines (SVMs), K-nearest neighbors (KNNs), decision trees (DTs), multiple layer perceptron (MLP), and convolutional neural networks (CNNs), and compares their performance. CNN exhibits the highest train accuracy at 97.808%, yet the lowest prediction accuracy at 90.08%. In contrast, SVM demonstrates the highest prediction accuracy of 95.5%. As such, an

Suicidal ideation is one of the most severe mental health issues faced by people all over the world. There are various risk factors involved that can lead to suicide. The most common & critical risk factors among them are depression, anxiety, social isolation and hopelessness. Early detection of these risk factors can help in preventing or reducing the number of suicides. Online social networking platforms like Twitter, Redditt and Facebook are becoming a new way for the people to express themselves freely without worrying about social stigma. This paper presents a methodology and experimentation using social media as a tool to analyse the suicidal ideation in a better way, thus helping in preventing the chances of being the victim o

Background: Substance use disorders (SUDs) are among the common psychiatric disorders and constitute a major public health concern. Iraqi’s were exposed to widespread violence and wars in the last decades. High prevalence of alcohol and substance use was reported recently in Baghdad. Research literature documented the association of SUDs with exposure to trauma events e.g. wars, terrorist attacks and natural disaster. Published articles on SUDs among prisoners in Iraq are scarce. Therefore, this work was carried out to report on SUDs among prisoners in Al-Diwania governorate and its relation to antisocial activity.
Methods: A total of 1200 prisoners in Al-Diwania civilian prison were included in the stu

Study aimed to determination of chitotriosidase-1 levels in Iraqi diabetic and diabetic patients with thyroid disorder. Also, study aimed to found relation correlation for chitotriosidase-1 with FSG, T3, T4 and TSH. Ninety subjects were including in this study. First group consisted of (30) healthy individuals who have no history of any thyroid disorders or diabetes mellitus as control group. Second group (G2) (n=30) patients with diabetic and hyperthyroidism as association disease, and third group (G3) (n=30) include patients with diabetic and hypothyroidism as association disease. Serum used in (FSG, T3, T4, TSH, and Chitotriosidase-1) determination. Results showed a significant elevation in patients’ groups (G2, G3) comparing t