Background: Appreciation of the crucial role of risk factors in the development of coronary artery disease (CAD) is one of the most significant advances in the understanding of this important disease. Extensive epidemiological research has established cigarette smoking, diabetes, hyperlipidemia, and hypertension as independent risk factors for CADObjective: To determine the prevalence of the 4 conventional risk factors(cigarette smoking, diabetes, hyperlipidemia, and hypertension) among patients with CAD and to determine the correlation of Thrombolysis in Myocardial Infarction (TIMI) risk score with the extent of coronary artery disease (CAD) in patients with unstable angina /non ST elevation myocardial infarction (UA/NSTEMI).Methods: We conducted a descriptive study among 100 patients admitted with UA/NSTEMI to three major cardiac centers in Iraq: Iraqi Centre for Heart Disease ,Ibn- Al-Bitar Hospital for cardiac surgery and Al -Nasyria Cardiac Centre from January 2010 to January 2o11.Frequency of each conventional risk factors and number of conventional risk factors present among patients with CAD, compared between men and women and by age are estimated at study entry. The TIMI risk score was stratified on seven standard variables. The extent of CAD was evaluated on angiography and significant CAD was defined as ≥ 70% stenosis in any one of the three major epicardial vessels and ≥50% in LMS.Results : Among 100 patients with UA/NSTEMI , 82% of patients have one or more risk factors and only 18%of patients lacked any of 4 conventional risk factors.Smoking is the most common risk factor in male patients while diabetes mellitus and dyslipidemia are common among female patients, and all these results are statistically significant.There were 64 % patients with TIMI score < 4 (low and intermediate TIMI risk score) and 36% patients with TIMI score >4 (high TIMI risk score). Patients with TIMI score > 4 were more likely to have significant three vessel CAD and LMS versus those with TIMI risk score < 4 who have less severe disease (single and two vessel disease).Conclusion: Antecedent major CAD risk factor exposures were very common among those who developed CAD emphasizing the importance of considering all major riskfactors in determining CAD risk estimation . Patients with a high TIMI risk score were more likely to have severe multivessel CAD compared with those with low or intermediate TIMI risk score. Hence, patients with TIMI score >4 should be referred for early invasive coronary evaluation to derive clinical benefit.Key words: unstable angina , Thrombolysis in Myocardial Infarction score, risk factors
The issue of penalized regression model has received considerable critical attention to variable selection. It plays an essential role in dealing with high dimensional data. Arctangent denoted by the Atan penalty has been used in both estimation and variable selection as an efficient method recently. However, the Atan penalty is very sensitive to outliers in response to variables or heavy-tailed error distribution. While the least absolute deviation is a good method to get robustness in regression estimation. The specific objective of this research is to propose a robust Atan estimator from combining these two ideas at once. Simulation experiments and real data applications show that the proposed LAD-Atan estimator
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It has increasingly been recognised that the future developments in geospatial data handling will centre on geospatial data on the web: Volunteered Geographic Information (VGI). The evaluation of VGI data quality, including positional and shape similarity, has become a recurrent subject in the scientific literature in the last ten years. The OpenStreetMap (OSM) project is the most popular one of the leading platforms of VGI datasets. It is an online geospatial database to produce and supply free editable geospatial datasets for a worldwide. The goal of this paper is to present a comprehensive overview of the quality assurance of OSM data. In addition, the credibility of open source geospatial data is discussed, highlight
... Show MoreThe Machine learning methods, which are one of the most important branches of promising artificial intelligence, have great importance in all sciences such as engineering, medical, and also recently involved widely in statistical sciences and its various branches, including analysis of survival, as it can be considered a new branch used to estimate the survival and was parallel with parametric, nonparametric and semi-parametric methods that are widely used to estimate survival in statistical research. In this paper, the estimate of survival based on medical images of patients with breast cancer who receive their treatment in Iraqi hospitals was discussed. Three algorithms for feature extraction were explained: The first principal compone
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Psychological research centers help indirectly contact professionals from the fields of human life, job environment, family life, and psychological infrastructure for psychiatric patients. This research aims to detect job apathy patterns from the behavior of employee groups in the University of Baghdad and the Iraqi Ministry of Higher Education and Scientific Research. This investigation presents an approach using data mining techniques to acquire new knowledge and differs from statistical studies in terms of supporting the researchers’ evolving needs. These techniques manipulate redundant or irrelevant attributes to discover interesting patterns. The principal issue identifies several important and affective questions taken from
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An analytical approach based on field data was used to determine the strength capacity of large diameter bored type piles. Also the deformations and settlements were evaluated for both vertical and lateral loadings. The analytical predictions are compared to field data obtained from a proto-type test pile used at Tharthar –Tigris canal Bridge. They were found to be with acceptable agreement of 12% deviation.
Following ASTM standards D1143M-07e1,2010, a test schedule of five loading cycles were proposed for vertical loads and series of cyclic loads to simulate horizontal loading .The load test results and analytical data of 1.95
... Show MoreGround-based active optical sensors (GBAOS) have been successfully used in agriculture to predict crop yield potential (YP) early in the season and to improvise N rates for optimal crop yield. However, the models were found weak or inconsistent due to environmental variation especially rainfall. The objectives of the study were to evaluate if GBAOS could predict YP across multiple locations, soil types, cultivation systems, and rainfall differences. This study was carried from 2011 to 2013 on corn (Zea mays L.) in North Dakota, and in 2017 in potatoes in Maine. Six N rates were used on 50 sites in North Dakota and 12 N rates on two sites, one dryland and one irrigated, in Maine. Two active GBAOS used for this study were GreenSeeker and Holl
... Show MoreIt has increasingly been recognised that the future developments in geospatial data handling will centre on geospatial data on the web: Volunteered Geographic Information (VGI). The evaluation of VGI data quality, including positional and shape similarity, has become a recurrent subject in the scientific literature in the last ten years. The OpenStreetMap (OSM) project is the most popular one of the leading platforms of VGI datasets. It is an online geospatial database to produce and supply free editable geospatial datasets for a worldwide. The goal of this paper is to present a comprehensive overview of the quality assurance of OSM data. In addition, the credibility of open source geospatial data is discussed, highlighting the diff
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The issue of penalized regression model has received considerable critical attention to variable selection. It plays an essential role in dealing with high dimensional data. Arctangent denoted by the Atan penalty has been used in both estimation and variable selection as an efficient method recently. However, the Atan penalty is very sensitive to outliers in response to variables or heavy-tailed error distribution. While the least absolute deviation is a good method to get robustness in regression estimation. The specific objective of this research is to propose a robust Atan estimator from combining these two ideas at once. Simulation experiments and real data applications show that the p
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The river water salinity is a major concern in many countries, and salinity can be expressed as total dissolved solids. So, the water salinity impact of the river is one of the major factors effects of water quality. Tigris river water salinity increase with streamline and time due to the decrease in the river flow and dam construction from neighboring countries. The major objective of this research to developed salinity model to study the change of salinity and its impact on the Al-Karkh, Sharq Dijla, Al-Karama, Al-Wathba, Al-Dora, and Al-Wihda water treatment plant along Tigris River in Baghdad city using artificial neural network model (ANN). The parameter used in a model built is (Turbidity, Ec, T.s, S.s, and TDS in)
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Objective: To evaluate two kinds of extraction (aqueous and ethanolic) for coriander using seeds, leaves and stems and
studying their antibacterial activity against nine different microorganisms.
Methodology: Coriander was selected to carry out this study. Seeds, leaves and stems were collected from local markets in
Baghdad then dried in shade for at least 10 days and grinded to fine powder. Aqueous hot extracts for 1hr. at (50
c) and
cold extracts for 24 hrs at (4
c) were performed by using seeds, leaves and stems then studied antibacterial effect against
nine different microorganisms by using well diffusion technique. Cold aqueous extracts of coriander seeds for 48 hrs. and
72 hrs and ethanolic extraction