Objective: To examined the common frequency of cervical cancer in Iraqi women. Study Design: Descriptive study Place and Duration of Study: This study was conducted at the Iraqi Cancer Agency and the Cancer Registry data from the Iraqi Ministry of Health provided assistance in data gathering from 1st April 2020 to 31st December 2021. Methods: The study examined 504 women diagnosed with cervical cancer. Their ages ranged from 20 to over 80 years. The data analysis employed descriptive statistics to determine the frequency, proportion, and incidence of cervical cancer. Results: The cervical cancer was predominantly caused by human papillomavirus in women in 2020 (1.29%) and 2021 (2.1%). In 2020, the number of cases of cervical can

Background: Cystatin C is recently considered to be a good predictor of cardiovascular morbidity and mortality in patients with coronary artery disease (CAD)Objectives: Correlation between cystatin and ischemic heart disease.Methods :One hundred forty patients (140) with ischemic heart disease admitted to thin study at Baghdad teaching hospital from the period June. 2011 to Jan. 2012. Those patients was categorized into three groups.Group (A): patients with ischemic heart failure.Group (B): Patients with myocardial infarction.Group (C) patients with unstable angina.All these groups were in comparison to fifty (50) healthy controls. Fasting serum citation (C) were measured in all patients and control in addition to all other routine inves

BACKGROUND: Sickle cell nephropathy, a heterogeneous group of renal abnormalities resulting from complex interactions of sickle cell disease (SCD)-related factors and non-SCD phenotype characteristics, is associated with an increased risk for morbidity and mortality. AIMS: The aims of this study were to determine the frequency of microalbuminuria (MA) among pediatric patients with SCD and to determine risk factors for MA among those patients. SUBJECTS AND METHODS: A case–control study was carried out on 120 patients with SCD, 2–18 years old, registered at Basrah Center for Hereditary Blood Diseases, and 132 age-and sex-matched healthy children were included as a control group. Investigations included complete blood panel, blood urea, se

Atherosclerotic cardiovascular disease (ACVD) is an inflammatory disease of the coronary arteries associated with atheroma formation, which can cause disability and often death. Periodontitis is ranked as the sixth most prevalent disease affecting humans affecting 740 million people worldwide. In the last few decades, researchers have focused on the effect of periodontal disease (PD) on cardiovascular disease. The aim of this review was to investigate the association between these two diseases. PD is a potential risk factor that may initiate the development, maturation, and instability of atheroma in the arteries. Two mechanisms were proposed to explain such association, either periodontal pathogens directly invade bloodstream or in

Precise forecasting of pore pressures is crucial for efficiently planning and drilling oil and gas wells. It reduces expenses and saves time while preventing drilling complications. Since direct measurement of pore pressure in wellbores is costly and time-intensive, the ability to estimate it using empirical or machine learning models is beneficial. The present study aims to predict pore pressure using artificial neural network. The building and testing of artificial neural network are based on the data from five oil fields and several formations. The artificial neural network model is built using a measured dataset consisting of 77 data points of Pore pressure obtained from the modular formation dynamics tester. The input variables

ABSTRACT:

Objectives: The study aims to know the effectiveness of the educational program in the patient’s adherence to medication and diet and to know the relationship between the effectiveness of the education program and their demographic data related to the patient’s age, gender, marital status, education level, occupation, monthly income and residence.

Methodology: A quasi -experimental design study was performed on patient who attended to Gastroenterology and Hepatology Teaching Hospital, from March 2021 to September 2021. The non-probability sampling including 50 patients for case study and 30 patients for control group. The questionnaire consists of 3 parts, part one the socio

Empirical and statistical methodologies have been established to acquire accurate permeability identification and reservoir characterization, based on the rock type and reservoir performance. The identification of rock facies is usually done by either using core analysis to visually interpret lithofacies or indirectly based on well-log data. The use of well-log data for traditional facies prediction is characterized by uncertainties and can be time-consuming, particularly when working with large datasets. Thus, Machine Learning can be used to predict patterns more efficiently when applied to large data. Taking into account the electrofacies distribution, this work was conducted to predict permeability for the four wells, FH1, FH2, F