It is considered as one of the statistical methods used to describe and estimate the relationship between randomness (Y) and explanatory variables (X). The second is the homogeneity of the variance, in which the dependent variable is a binary response takes two values  (One when a specific event occurred and zero when that event did not happen) such as (injured and uninjured, married and unmarried) and that a large number of explanatory variables led to the emergence of the problem of linear multiplicity that makes the estimates inaccurate, and the method of greatest possibility and the method of declination of the letter was used in estimating A double-response logistic regression model by adopting the Jackna

It is considered as one of the statistical methods used to describe and estimate the relationship between randomness (Y) and explanatory variables (X). The second is the homogeneity of the variance, in which the dependent variable is a binary response takes two values  (One when a specific event occurred and zero when that event did not happen) such as (injured and uninjured, married and unmarried) and that a large number of explanatory variables led to the emergence of the problem of linear multiplicity that makes the estimates inaccurate, and the method of greatest possibility and the method of declination of the letter was used in estimating A double-response logistic regression model by adopting the Jackna

In this study, gold nanoparticles were synthesized in a single step biosynthetic method using aqueous leaves extract of thymus vulgaris L. It acts as a reducing and capping agent. The characterizations of nanoparticles were carried out using UV-Visible spectra, X-ray diffraction (XRD) and FTIR. The surface plasmon resonance of the as-prepared gold nanoparticles (GNPs) showed the surface plasmon resonance centered at 550[Formula: see text]nm. The XRD pattern showed that the strong four intense peaks indicated the crystalline nature and the face centered cubic structure of the gold nanoparticles. The average crystallite size of the AuNPs was 14.93[Formula: see text]nm. Field emission scanning electron microscope (FESEM) was used to s

The logistic regression model is one of the oldest and most common of the regression models, and it is known as one of the statistical methods used to describe and estimate the relationship between a dependent random variable and explanatory random variables. Several methods are used to estimate this model, including the bootstrap method, which is one of the estimation methods that depend on the principle of sampling with return, and is represented by a sample reshaping that includes (n) of the elements drawn by randomly returning from (N) from the original data, It is a computational method used to determine the measure of accuracy to estimate the statistics, and for this reason, this method was used to find more accurate estimates. The ma

Human cytomegalovirus (HCMV) has a worldwide distribution and extremely common infections. The presence of HCMV genome and antigens has been detected in many kinds of human cancers especially breast cancer. In Iraq, the incidence of breast cancer generally exceeds any other type of malignancies among Iraqi population. The study was performed in the period between October 2016 and June 2017 in Central public health laboratory/Baghdad. It involve samples from 90 women including 60 breast cancer patients, 20 benign tumor patients, and 10 normal breast tissues. A blood sample was obtained from each woman included in this study. Anti-HCMV IgG antibody was presented in 9/10 (90%) of normal women, benign breast tumor patients 19/20 (95%) and malig

Human Cytomegalovirus (HCMV) is an enveloped ubiquitous ds-DNA virus that has been implicated in several types of malignancies. The current work was conducted in the period extending from (November 2018 to the end of October 2019) and aimed to assess the frequency of glycoprotein N (gN) genotypes of HCMV. A total number of 91serum and plasma specimens were collected to fulfill this purpose from females (71 breast cancer patients, and a control group of 20 females) attending Al-Amal hospital for cancer management and Baghdad teaching hospital. The molecular part of this data was achieved through both PCR and Multiplex PCR for detection of HCMV gN (UL73) entire gene as well as for genotyping. gN was detected in 36/71 (50.7%) of breast cancer

Breast cancer is the most commonly diagnosed cancer and remains one of the main reasons of cancer-related mortality in women worldwide. KRAS variant rs61764370 (T>G) is associated with an increased risk of occurrence of many cancers, Here The case-control study was accomplished on 135 women including 45 women with breast cancer patients, 45 women with benign breast lesions and 45 healthy women to analyze the association of KRAS variant rs (61764370 T>G) with breast cancer. LCS 6 variant in KRAS gene was amplified by using specific primers, then genotype was detected after sequencing the PCR products. The results showed that the genotype and allele frequency of TT and GT allele of  KRAS

Breast tumors patients generally have more oxidative stress than normal females. This was clear from a highly significant elevation (P<0.05) in malondialdehyde level in RBCs, serum and tissue of all patients groups with breast cancer as compared with control group. In this study we had found that free radicals in malignant breast tumors were higher than benign tumors, therefore the MDA might be used as a marker for prognosis of the disease.

Breast cancer was one of the most common reasons for death among the women in the world. Limited awareness of the seriousness of this disease, shortage number of specialists in hospitals and waiting the diagnostic for a long period time that might increase the probability of expansion the injury cases. Consequently, various machine learning techniques have been formulated to decrease the time taken of decision making for diagnoses the breast cancer and that might minimize the mortality rate. The proposed system consists of two phases. Firstly, data pre-processing (data cleaning, selection) of the data mining are used in the breast cancer dataset taken from the University of California, Irvine machine learning repository in this stage we