Breast cancer is one of the most common cancers in females. In Iraq there are noticeable elevation in incidence rates and prevalence of advanced stages of breast cancer. Ferritin is intracellular iron storage protein abundant in circulation and its main application in differential diagnosis of anemia.

The level of serum ferritin was found raised in various cancers including breast cancer. The aim of this study was to assess whether the serum ferritin concentration would be altered in Iraqi women with breast cancer and it could be related to progression of disease.

Sixty eight females participated in this study. The mean age of these females was 53.25± 9.52 .The level of serum ferritin was measured in 24

Abstract 

This paper presents an intelligent model reference adaptive control (MRAC) utilizing a self-recurrent wavelet neural network (SRWNN) to control nonlinear systems. The proposed SRWNN is an improved version of a previously reported wavelet neural network (WNN). In particular, this improvement was achieved by adopting two modifications to the original WNN structure. These modifications include, firstly, the utilization of a specific initialization phase to improve the convergence to the optimal weight values, and secondly, the inclusion of self-feedback weights to the wavelons of the wavelet layer. Furthermore, an on-line training procedure was proposed to enhance the control per

         The aims of the present study are to evaluate the levels of CA19-9 in sera and tissues' homogenate of breast and thyroid benign patients in order to assess its use as an early diagnostic parameter in differentiation between malignant and benign cases. The study was conducted on 8 patients with breast benign tumor and 8 patients with thyroid benign tumor, by the enzyme linked immunosorbent assay (ELISA) technique. The results of CA19-9 levels in sera were (15 ±1.58 and 10.67 ±2.08)U/ml respectively compared with serum CA19-9 levels of control group which was 7.74 ±4.92 U/ml, the results were found to be highly significantly in breast tumor patients and non significantly in thyroid

To determine the relationship between Helicobacter pylori infection and skin disorders, sixty six patients who suffering from skin diseases include chronic urticarial (CU) and atopic dermatitis (AD) who attended at Dermatological Clinic/ Al-Numan Teaching Hospital from the beginning of October 2015 to the end of January 2016 with age (6-62) have been investigated and compared to twenty two samples of apparently healthy individuals were studied as control group. All the studied groups were subjected to measurement of antiHelicobacter pylori IgG antibodies by enzyme linked immuno sorbent assay (ELISA) and detection of 16S rRNA and CagA genes by using singleplex and multiplex PCR methods. The results of current study revealed that there was a

With the growth of mobile phones, short message service (SMS) became an essential text communication service. However, the low cost and ease use of SMS led to an increase in SMS Spam. In this paper, the characteristics of SMS spam has studied and a set of features has introduced to get rid of SMS spam. In addition, the problem of SMS spam detection was addressed as a clustering analysis that requires a metaheuristic algorithm to find the clustering structures. Three differential evolution variants viz DE/rand/1, jDE/rand/1, jDE/best/1, are adopted for solving the SMS spam problem. Experimental results illustrate that the jDE/best/1 produces best results over other variants in terms of accuracy, false-positive rate and false-negative

Determining the face of wearing a mask from not wearing a mask from visual data such as video and still, images have been a fascinating research topic in recent decades due to the spread of the Corona pandemic, which has changed the features of the entire world and forced people to wear a mask as a way to prevent the pandemic that has calmed the entire world, and it has played an important role. Intelligent development based on artificial intelligence and computers has a very important role in the issue of safety from the pandemic, as the Topic of face recognition and identifying people who wear the mask or not in the introduction and deep education was the most prominent in this topic. Using deep learning techniques and the YOLO (”You on

Several Intrusion Detection Systems (IDS) have been proposed in the current decade. Most datasets which associate with intrusion detection dataset suffer from an imbalance class problem. This problem limits the performance of classifier for minority classes. This paper has presented a novel class imbalance processing technology for large scale multiclass dataset, referred to as BMCD. Our algorithm is based on adapting the Synthetic Minority Over-Sampling Technique (SMOTE) with multiclass dataset to improve the detection rate of minority classes while ensuring efficiency. In this work we have been combined five individual CICIDS2017 dataset to create one multiclass dataset which contains several types of attacks. To prove the eff