Objective: Breast cancer is regarded as a deadly disease in women causing lots of mortalities. Early diagnosis of breast cancer with appropriate tumor biomarkers may facilitate early treatment of the disease, thus reducing the mortality rate. The purpose of the current study is to improve early diagnosis of breast by proposing a two-stage classification of breast tumor biomarkers fora sample of Iraqi women.

Methods: In this study, a two-stage classification system is proposed and tested with four machine learning classifiers. In the first stage, breast features (demographic, blood and salivary-based attributes) are classified into normal or abnormal cases, while in the second stage the abnormal breast cases are

The current study is the identification and isolation dermatophyte species in clinical isolates by both Sabouraud’s Dextrose Agar (SDA) and on Dermatophyte Test Medium (DTM). Clinical specimens of hair, nails and skin scales were collected from patients with dermatophytosis and submitted to direct microscopic examination after immersion in 20% of potassium hydroxide solution. The clinical specimens were cultured on SDA containing chloramphenicol and cycloheximide, and on DTM. Tinea corporis showed the highest prevalent dermatophyte infection among patients (26.7%), followed by Tinea pedis (23.3%), whereas Tinea manuum exhibited the lowest fungal infection (6.7 %). Rural areas revealed the highest prevalence of dermatophyte in

Background: This study is to evaluate the necessity of prescribing prophylactic antibiotics for nasal packing in spontaneous epistaxis. There are few published papers of infective complications in such patients.

Methods: This prospective study analysed 149 consecutive patients admitted to AL-Kindy teaching hospital with spontaneous, epistaxis, who underwent nasal packing  over 2 years period . in the first  year, 78 patients received prophylactic antibiotics , In the second  year 71 patients were not given prophylatic antibiotics.  Exclusion criteria included antibiotics prescribed for unrelated  pathology and post-operative epistaxis. Signs and symptoms of acute otitis m

A descriptive study, which was using an assessment approach, was conducted for the
determination of the impact of rheumatoid arthritis and osteoarthritis patient’s functional disability
upon their life style. The study was carried out at the Rheumatology and outpatients clinics of ALKarama
Teaching Hospital, Baghdad Teaching Hospital AL-Kindey Teaching Hospital and Specialized
surgeries Teaching Hospital for the period of October 15th 2003 through May 13th 2004 in Baghdad
City. A purposive (non-probability) sample of (245) arthritis patients which was comprised (111)
rheumatoid arthritis patients and (134) osteoarthritis patients, was selected out of the early stated
settings. The questionnaire was comprised of

  The great scientific progress has led to widespread Information as information accumulates in large databases is important in trying to revise and compile this vast amount of data and, where its purpose to extract hidden information or classified data under their relations with each other in order to take advantage of them for technical purposes.

      And work with data mining (DM) is appropriate in this area because of the importance of research in the (K-Means) algorithm for clustering data in fact applied with effect can be observed in variables by changing the sample size (n) and the number of clusters (K)

In this work ,medical zinc oxide was produced from zinc scraps instead of traditional method which used for medical applications such as skin diseases, Iraq is importing around 50 ton/year for samarra plant the producted powder has apartical size less than 5 micron and the purity was more than 99.98%,also apilot plant of yield capacitiy 15 kg/8hours wsa designed and manufactured .

The need for image compression is always renewed because of its importance in reducing the volume of data; which in turn will be stored in less space and transferred more quickly though the communication channels.
In this paper a low cost color image lossy color image compression is introduced. The RGB image data is transformed to YUV color space, then the chromatic bands U & V are down-sampled using dissemination step. The bi-orthogonal wavelet transform is used to decompose each color sub band, separately. Then, the Discrete Cosine Transform (DCT) is used to encode the Low-Low (LL) sub band. The other wavelet sub bands are coded using scalar Quantization. Also, the quad tree coding process was applied on the outcomes of DCT and

Abstract:

     The use of economic resources enjoyed Iraq by especially oil resources, which constitute the main source of financial revenue, would the economic surplus outside the oil sector increases by mobilizing and rallying the labor power and turn it into an access capitalism, , was the cause of "the inaction of the productive sectors of the economy, made the investment planning process and even investment in human capital was not rationality with the increasing number of unemployed, particularly certificates and specializations high campaign, direction of the government towards market liberalism after 2003 through the, was focused not follow a clear economic policies, and the absence of planning

     In this work, the methods (Moments, Modified Moments, L-Moments, Percentile, Rank Set sampling and Maximum Likelihood) were used to estimate the reliability function and the two parameters of the Transmuted Pareto (TP) distribution. We use simulation to generate the required data from three cases this indicates  sample size , and it replicates  for the real value for parameters, for reliability times values  we take .

Results were compared by using mean square error (MSE), the result appears as follows :

The best methods are Modified Moments, Maximum likelihood and L-Moments in first case, second case and third case respectively.

Heart disease identification is one of the most challenging task that requires highly experienced cardiologists. However, in developing nations such as Ethiopia, there are a few cardiologists and heart disease detection is more challenging. As an alternative solution to cardiologist, this study proposed a more effective model for heart disease detection by employing random forest and sequential feature selection (SFS). SFS is an effective approach to improve the performance of random forest model on heart disease detection. SFS removes unrelated features in heart disease dataset that tends to mislead random forest model on heart disease detection. Thus, removing inappropriate and duplicate features from the training set with sequential f