Back ground : Coronary artery diseases are not uncommon in the presence of right bundle branch block.
Aim : The aim of this study is to assess the findings of coronary angiography in patients with chest pain and right bundle branch block.
Methods : The study involved review of case sheets and coronary angiography of one hundred patients, who underwent coronary angiography due to chest pain suspected to have
coronary artery diseases (CAD) , fifty patients of them had right bundle branch block (RBBB) , the other fifty did not have RBBB , those 100 patients were presented to Ibin Al Bitar hospital
for cardiac surgery from January 2004 to June 2006. History, clinical examinations, electrocardiogram (ECG) , ECG exercise tests (EET) echocardiogram (ECHO) and coronary angiography had been performed.
Results : Mean age of patients was 53± 10.6 years, 84% were male , hypertension, diabetes mellitus, and smoking as risk factors were present as 30%, 32% and 48% respectively. 58% of
patients presented with chronic stable angina (CSA) while 42% with acute coronary syndrome (ACS), ECHO showed that left ventricular dysfunction (LVD) was present in 34%, EET was
positive in 11 of the 23 patients (47.8%) who were able to perform EET. Normal coronary angiography found in 20% of patients and there were no significant difference in coronary
angiographic findings between patients with and without RBBB.
Conclusion : RBBB of indeterminate age has no significant impact on clinical and haemodynamic characteristics of CAD patients and it may be incidental finding.
Background: celiac disease, is an autoimmune inflammatory disease of the small intestine that is precipitated by the ingestion of gluten, a component of wheat protein, in genetically susceptible persons. Serologic tests for antibodies against Endomysium, Reticulin, and Gliadin identify most patients with the disease. Early diagnosis and management are important to forestall serious consequences of malabsorption, such as osteoporosis and anemia
Aims of the study: This study compared the sensitivity, specificity, and predictive value of, anti-reticulin and anti-gliadin antibodies according to anti endomysium antibodies , in consecutive patients investigated for celiac disease antibodies.
Patient& Methods: Total 509 patients (236
Heart disease is a non-communicable disease and the number 1 cause of death in Indonesia. According to WHO predictions, heart disease will cause 11 million deaths in 2020. Bad lifestyle and unhealthy consumption patterns of modern society are the causes of this disease experienced by many people. Lack of knowledge about heart conditions and the potential dangers cause heart disease attacks before any preventive measures are taken. This study aims to produce a system for Predicting Heart Disease, which benefits to prevent and reduce the number of deaths caused by heart disease. The use of technology in the health sector has been widely practiced in various places and one of the advanced technologies is machine lea
... Show MoreGranting rights, especially procedural, to victims before the International Criminal Court (ICC) is a fundamental departure from international criminal courts, whether (temporary or mixed military courts), and for the first time in the history of international criminal justice, victims can participate in reparations procedures before the Criminal Court. Where they can express their views and concerns at all stages of the proceedings, as the 1998 Rome Statute made the victim an active party in the court proceedings by recognizing a number of rights, such as the right to participate in the trial, the right to protection, and the right to legal representation, As well as the right to reparation or compensation.
In this paper, an algorithm for binary codebook design has been used in vector quantization technique, which is used to improve the acceptability of the absolute moment block truncation coding (AMBTC) method. Vector quantization (VQ) method is used to compress the bitmap (the output proposed from the first method (AMBTC)). In this paper, the binary codebook can be engender for many images depending on randomly chosen to the code vectors from a set of binary images vectors, and this codebook is then used to compress all bitmaps of these images. The chosen of the bitmap of image in order to compress it by using this codebook based on the criterion of the average bitmap replacement error (ABPRE). This paper is suitable to reduce bit rates
... Show MoreThis research aims to solve the nonlinear model formulated in a system of differential equations with an initial value problem (IVP) represented in COVID-19 mathematical epidemiology model as an application using new approach: Approximate Shrunken are proposed to solve such model under investigation, which combines classic numerical method and numerical simulation techniques in an effective statistical form which is shrunken estimation formula. Two numerical simulation methods are used firstly to solve this model: Mean Monte Carlo Runge-Kutta and Mean Latin Hypercube Runge-Kutta Methods. Then two approximate simulation methods are proposed to solve the current study. The results of the proposed approximate shrunken methods and the numerical
... Show MoreIn recent years, predicting heart disease has become one of the most demanding tasks in medicine. In modern times, one person dies from heart disease every minute. Within the field of healthcare, data science is critical for analyzing large amounts of data. Because predicting heart disease is such a difficult task, it is necessary to automate the process in order to prevent the dangers connected with it and to assist health professionals in accurately and rapidly diagnosing heart disease. In this article, an efficient machine learning-based diagnosis system has been developed for the diagnosis of heart disease. The system is designed using machine learning classifiers such as Support Vector Machine (SVM), Nave Bayes (NB), and K-Ne
... Show MoreThe main goal of this research is to determine the impact of some variables that we believe that they are important to cause renal failuredisease by using logistic regression approach.The study includes eight explanatory variables and the response variable represented by (Infected,uninfected).The statistical program SPSS is used to proform the required calculations
The theory of Multi-Criteria Decision Making (MCDM) was introduced in the second half of the twentieth century and aids the decision maker to resolve problems when interacting criteria are involved and need to be evaluated. In this paper, we apply MCDM on the problem of the best drug for rheumatoid arthritis disease. Then, we solve the MCDM problem via -Sugeno measure and the Choquet integral to provide realistic values in the process of selecting the most appropriate drug. The approach confirms the proper interpretation of multi-criteria decision making in the drug ranking for rheumatoid arthritis.
Background/Objectives: The purpose of this study was to classify Alzheimer’s disease (AD) patients from Normal Control (NC) patients using Magnetic Resonance Imaging (MRI). Methods/Statistical analysis: The performance evolution is carried out for 346 MR images from Alzheimer's Neuroimaging Initiative (ADNI) dataset. The classifier Deep Belief Network (DBN) is used for the function of classification. The network is trained using a sample training set, and the weights produced are then used to check the system's recognition capability. Findings: As a result, this paper presented a novel method of automated classification system for AD determination. The suggested method offers good performance of the experiments carried out show that the
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