Background: Acute appendicitis is the most common abdominal surgical emergency. The diagnosis of this condition is still essentially clinical and there is difficulty in the clinical diagnosis, especially among elderly, children and patients with a typical presentation, so early and accurate diagnosis of acute appendicitis is important to avoid its complications.Objectives: To evaluate the degree of accuracy of Alvarado scoring system in the diagnosis of acute appendicitis.Method: Two hundred patients were admitted to the Alkindy Teaching Hospital from January 2011 to april 2014- presented with symptoms and signs suggestive of acute appendicitis. After examination and investigations all patients were given a score according to Alvarado sc

Article information: COVID-19 has roused the scientic community, prompting calls for immediate solutions to avoid the infection or at least reduce the virus's spread. Despite the availability of several licensed vaccinations to boost human immunity against the disease, various mutated strains of the virus continue to emerge, posing a danger to the vaccine's ecacy against new mutations. As a result, the importance of the early detection of COVID-19 infection becomes evident. Cough is a prevalent symptom in all COVID-19 mutations. Unfortunately, coughing can be a symptom of various of diseases, including pneumonia and inuenza. Thus, identifying the coughing behavior might help clinicians diagnose the COVID-19 infection earlier and distinguish

Background: breast cancer is commonest cancer globally and the 1st cancer in Iraq among females, its management and prognosis depend on early diagnosis, the traditional method was excisional biopsy which is expensive and invasive leading to delayed diagnosis, FNAB is cheap nom invasive more acceptable to women, Aim of the study: to test the reliability of FNAB in preoperative diagnosis of breast lump.

Methodology: This is a retrospective study of 204 cases, 102 breast cancer cases and 102 benign breast lesions, taken between Jan. 2017 – Nov. 2017. The sample taken from the breast cancer early detection center in  Al-Alwiyaa maternity teaching hospital, during the year 2017

In this work an enzyme linked immunosorbent assay (ELISA) technique has been used for detection of some inflammatory markers in serum of acute coronary syndrome (ACS)-Patients Admitted to the cardiac care unit (CCU) of Iraqi Centre For Heart Diseases and Ibn AlNafees Teaching Hospital. The present method includes quantitative measurement of interleukine-6 (IL-6) and C-reactive protein (CRP), as their increase during symptoms may be responsible for identifying the mechanism of myocardial damag, in addition to their best performance than other quantitative tests perhaps due to their association with atherosclerotic process that belongs to the endothelial dysfunction. Aim of this study is to estimate the prevalence and correlation of IL-6 w

Nonlinear time series analysis is one of the most complex problems ; especially the nonlinear autoregressive with exogenous variable (NARX) .Then ; the problem of model identification and the correct orders determination considered the most important problem in the analysis of time series . In this paper , we proposed splines  estimation method for model identification , then we used three criterions for the correct orders determination. Where ; proposed method used to estimate the additive splines for model identification , And the rank determination depends on the additive property  to avoid the problem of curse dimensionally . The proposed method is one of the nonparametric methods , and the simulation results give a

Nowadays, internet security is a critical concern; the One of the most difficult study issues in network security is "intrusion detection". Fight against external threats. Intrusion detection is a novel method of securing computers and data networks that are already in use. To boost the efficacy of intrusion detection systems, machine learning and deep learning are widely deployed. While work on intrusion detection systems is already underway, based on data mining and machine learning is effective, it requires to detect intrusions by training static batch classifiers regardless considering the time-varying features of a regular data stream. Real-world problems, on the other hand, rarely fit into models that have such constraints. Furthermor

Fuzzy logic is used to solve the load flow and contingency analysis problems, so decreasing computing time and its the best selection instead of the traditional methods. The proposed  method is very accurate with outstanding computation time, which made the fuzzy load flow (FLF) suitable for real time application for small- as well as large-scale power systems. In addition that, the FLF efficiently able to solve load flow problem of ill-conditioned power systems and contingency analysis. The FLF method using Gaussian membership function requires less number of iterations and less computing time than that required in the FLF method using triangular membership function. Using sparsity technique for the input Ybus sparse matrix data gi

Leishmaniasis is a transmissible infection brought about by an obligatory intracellular protozoan from the genus Leishmania.  It occurs worldwide in tropical and subtropical regions and can be burdensome in resource-constrained countries. The infection ranges in severity from mild cutaneous lesions to more severe and sometimes life-threatening visceral and distorting mucocutaneous sicknesses. Importantly, cutaneous leishmaniasis (CL) is prevalent in the Middle East with a pooled prevalence of 12%. It imposes a significant health and socioeconomic burden