In this research, we find the Bayesian formulas and the estimation of Bayesian expectation for product system of Atlas Company.  The units of the system have been examined by helping the technical staff at the company and by providing a real data the company which manufacturer the system.  This real data include the failed units for each drawn sample, which represents the total number of the manufacturer units by the company system.  We calculate the range for each estimator by using the Maximum Likelihood estimator.  We obtain that the expectation-Bayesian estimation is better than the Bayesian estimator of the different partially samples which were drawn from the product system after  it checked by the

         Sera samples were collected from 60 children aged 4-60 months, all were clinically and serologically proven cases of visceral leishmaniasis, as well as  from 10 healthy children, all were seronegative with no history of parasitic infection who serve as a control during the study. Serum total protein and albumin were measured and compared between the control and visceral leishmaniasis patients. Serum protein profiles have been investigated using the conventional sodium dodecyl sulphate – polyacrylamide gel electrophoresis (SDS-PAGE).  Serum of control group showed the specific protein pattern with five protein bands, while serum protein profile in visceral leishmaniasis pat

Lipid disorders and cardiovascular disease (CVD) risk are known to be increased in patients with diabetes mellitus. The effects of statins on serum lipid levels are well known; however, previous studies did not compare the effects of statins on serum lipid levels in diabetic patients with non-diabetic patients. To investigate the effects of Atorvastatin on serum lipid profiles in hyperlipidemic patients with type 2 diabetes mellitus in comparison with hyperlipidemic patients without diabetes.This study was conducted on 33 type 2 diabetic patients & 34 non-diabetic patients; their age range was 40-80 years, all of them were hyperlipidemic, who had been administered 10, 20, & 40 mg daily of Atorvastatin and completed a 6-month foll

Today’s modern medical imaging research faces the challenge of detecting brain tumor through Magnetic Resonance Images (MRI). Normally, to produce images of soft tissue of human body, MRI images are used by experts. It is used for analysis of human organs to replace surgery. For brain tumor detection, image segmentation is required. For this purpose, the brain is partitioned into two distinct regions. This is considered to be one of the most important but difficult part of the process of detecting brain tumor. Hence, it is highly necessary that segmentation of the MRI images must be done accurately before asking the computer to do the exact diagnosis. Earlier, a variety of algorithms were developed for segmentation of MRI images by usin

Background: Abdominal symptoms are possibly the most frequent of all symptoms encountered in surgical practice.  Pain is the most common of all abdominal symptoms.  Causes of acute abdominal pain include both medical and surgical. Most symptoms arise from intra-abdominal organs or systems while some may originate extra abdominally and are then referred to the abdomen. Medical causes of abdominal pain are encountered more frequently.

Objective: To study the causes of acute abdominal pain in patients attending emergency department in Al- Imamain Al- Kadhimain Medical City.

Type of the study: A prospective cross sectional study

Meth

Alzheimer’s disease (AD) is an age-related progressive and neurodegenerative disorder, which is characterized by loss of memory and cognitive decline. It is the main cause of disability among older people. The rapid increase in the number of people living with AD and other forms of dementia due to the aging population represents a major challenge to health and social care systems worldwide. Degeneration of brain cells due to AD starts many years before the clinical manifestations become clear. Early diagnosis of AD will contribute to the development of effective treatments that could slow, stop, or prevent significant cognitive decline. Consequently, early diagnosis of AD may also be valuable in detecting patients with dementia who have n

Magnetic  Resonance  Imaging  (MRI)  is  one  of  the  most important diagnostic tool. There are many methods to segment the

tumor of human brain. One of these, the conventional method that uses pure image processing techniques that are not preferred because they need human interaction for accurate segmentation. But unsupervised methods do not require any human interference and can segment   the   brain   with   high   precision.   In   this   project,   the unsupervised  classification methods have been used in order to detect the tumor  disease from MRI images.    These metho