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

A new synthesis of Schiff (K) 6 and Mannich bases (Q) 7 had formed compound (Q) 7 by reacting compound (K) with N-methylaniline at the presence of formalin 35% to given Mannich base (Q). Additionally, new complexes were formed by reacting Schiff base (K) with metal salts CuCl2·2H2O, PdCl2·2H2O, and PtCl6·6H2O by 2:1 of M:L ratio. New ligands and their complexes were characterized, exanimated, and confirmed through several techniques, including FTIR, UV-visible, 1H-NMR, 13C-NMR spectroscopy, CHN analysis, FAA, TG, molar conductivity, and magnetic susceptibility. These compounds and their complexes were screened against breast cancer cells. It was determined that several of these compounds had a significant anti-breast cancer effec

     The lymphotoxin alpha is a highly polymorphic gene and any genetic variation in it may lead to an increased production of cytokine LTA thus helping tumor development and progression. The aim of this work was to investigate the association of LTA polymorphism with the risk of breast cancer among Iraqi women. The findings of this study demonstrated that the age group > 50 years old formed 52% of the breast cancer patients (P <0.001). Hardy–Weinberg equilibrium analysis revealed that genotype frequencies of most SNPs in BC patients and HC were consistent with HWE. No association was found between LTA polymorphisms and BC. Moreover, seven haplotypes were detected in BC group. However, only one of them developed sign

Background: Breast cancer is the commonest type of malignancy among women worldwide and in Iraq. Tru-cut needle biopsy technique provides adequate tissue for histopathological diagnosis of suspected breast lumps and assessment of hormonal receptors (estrogen, progesterone and HER2neu) prior to surgical operation.
Objectives: To assess estrogen, progesterone andHER2neu expression using breast cancer tissue specimens obtained by tru-cut biopsy, to correlate the findings with clinicopathological parameters of known prognostic significance in breast cancer patients.
Patients and Methods: This prospective study was held within the Main Referral Center for Early Detection of Breast Tumors/Medical City Teachi

Background: Breast cancer is the commonest cancer in women. In radiotherapy practice, it comprises 25% of patient caseload. This makes understanding the breast irradiation toxicities of prime importance. Early radiation toxicities occur during treatment and up to six months after treatment finished.
Objectives: assessment of the early side effects of adjuvant external beam radiotherapy (EBRT) in breast cancer patients.
Patients and Methods: A cross sectional survey with analytic component conducted on 60 patients treated in the oncology teaching hospital of medical city from January to April 2016.
Results: The most prevalent toxicities were radiation dermatitis, fatigue, pain, sore throat, nausea, dysphagia,&

Background: - Recurrent breast cancer is cancer that comes back following initial treatment. Risk factors of recurrence are lymph node involvement, larger tumor size, positive or close tumor margins, and lack of radiation treatment following lumpectomy, younger age and inflammatory breast cancer.
Objective: Asses the rate of recurrence for early breast cancer in Iraqi female patients, in relation to certain risk factors.
Patients and methods: A prospective study was conducted on 100 consecutive female patients, with stage I and stage II breast cancer treated by mastectomy and axillary dissection by the same team. Patients were assessed postoperatively every three months and recurrences were detected by physical examination and ultr

<p>Analyzing X-rays and computed tomography-scan (CT scan) images using a convolutional neural network (CNN) method is a very interesting subject, especially after coronavirus disease 2019 (COVID-19) pandemic. In this paper, a study is made on 423 patients’ CT scan images from Al-Kadhimiya (Madenat Al Emammain Al Kadhmain) hospital in Baghdad, Iraq, to diagnose if they have COVID or not using CNN. The total data being tested has 15000 CT-scan images chosen in a specific way to give a correct diagnosis. The activation function used in this research is the wavelet function, which differs from CNN activation functions. The convolutional wavelet neural network (CWNN) model proposed in this paper is compared with regular convol

   Regarding to the computer system security, the intrusion detection systems are fundamental components for discriminating attacks at the early stage. They monitor and analyze network traffics, looking for abnormal behaviors or attack signatures to detect intrusions in early time. However, many challenges arise while developing flexible and efficient network intrusion detection system (NIDS) for unforeseen attacks with high detection rate. In this paper, deep neural network (DNN) approach was proposed for anomaly detection NIDS. Dropout is the regularized technique used with DNN model to reduce the overfitting. The experimental results applied on NSL_KDD dataset. SoftMax output layer has been used with cross entropy loss funct

This search has introduced the techniques of multi-wavelet transform and neural network for recognition 3-D object from 2-D image using patches. The proposed techniques were tested on database of different patches features and the high energy subband of discrete multi-wavelet transform DMWT (gp) of the patches. The test set has two groups, group (1) which contains images, their (gp) patches and patches features of the same images as a part of that in the data set beside other images, (gp) patches and features, and group (2) which contains the (gp) patches and patches features the same as a part of that in the database but after modification such as rotation, scaling and translation. Recognition by back propagation (BP) neural network as com