Objective This research investigates Breast Cancer real data for Iraqi women, these data are acquired manually from several Iraqi Hospitals of early detection for Breast Cancer. Data mining techniques are used to discover the hidden knowledge, unexpected patterns, and new rules from the dataset, which implies a large number of attributes. Methods Data mining techniques manipulate the redundant or simply irrelevant attributes to discover interesting patterns. However, the dataset is processed via Weka (The Waikato Environment for Knowledge Analysis) platform. The OneR technique is used as a machine learning classifier to evaluate the attribute worthy according to the class value. Results The evaluation is performed using a training data rather than cross validation. The decision tree algorithm J48 is applied to detect and generate the pattern of attributes, which have the real effect on the class value. Furthermore, the experiments are performed with three machine learning algorithms J48 decision tree, simple logistic, and multilayer perceptron using 10-folds cross validation as a test option, and the percentage of correctly classified instances as a measure to determine the best one from them. As well as, this investigation used the iteration control to check the accuracy gained from the three mentioned above algorithms. Hence, it explores whether the error ratio is decreasing after several iterations of algorithm execution or not. Conclusion It is noticed that the error ratio of classified instances are decreasing after 5-10 iterations, exactly in the case of multilayer perceptron algorithm rather than simple logistic, and decision tree algorithms. This study realized that the TPS_pre is the most common effective attribute among three main classes of examined dataset. This attribute highly indicates the BC inflammation.
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In This Paper, some semi- parametric spatial models were estimated, these models are, the semi – parametric spatial error model (SPSEM), which suffer from the problem of spatial errors dependence, and the semi – parametric spatial auto regressive model (SPSAR). Where the method of maximum likelihood was used in estimating the parameter of spatial error ( λ ) in the model (SPSEM), estimated the parameter of spatial dependence ( ρ ) in the model ( SPSAR ), and using the non-parametric method in estimating the smoothing function m(x) for these two models, these non-parametric methods are; the local linear estimator (LLE) which require finding the smoo
... Show MoreThe advancements in Information and Communication Technology (ICT), within the previous decades, has significantly changed people’s transmit or store their information over the Internet or networks. So, one of the main challenges is to keep these information safe against attacks. Many researchers and institutions realized the importance and benefits of cryptography in achieving the efficiency and effectiveness of various aspects of secure communication.This work adopts a novel technique for secure data cryptosystem based on chaos theory. The proposed algorithm generate 2-Dimensional key matrix having the same dimensions of the original image that includes random numbers obtained from the 1-Dimensional logistic chaotic map for given con
... Show MoreUnderwater Wireless Sensor Networks (UWSNs) have emerged as a promising technology for a wide range of ocean monitoring applications. The UWSNs suffer from unique challenges of the underwater environment, such as dynamic and sparse network topology, which can easily lead to a partitioned network. This results in hotspot formation and the absence of the routing path from the source to the destination. Therefore, to optimize the network lifetime and limit the possibility of hotspot formation along the data transmission path, the need to plan a traffic-aware protocol is raised. In this research, we propose a traffic-aware routing protocol called PG-RES, which is predicated on the ideas of Pressure Gradient and RESistance concept. The proposed
... Show MoreThe present study aims to estimating the prevalence of autoimmune thyroid disorders in Iraqi infertile women with polycystic ovary syndrome (PCOS). Eighty-five Iraqi women, with age range (19-45) years, were divided into three groups; first group included 33 women with PCOS; second group included 30 women without PCOS; while third group included 22 fertile women as controls. The clinical data [age, body mass index (BMI), and menstrual status] have been recorded. Blood samples were collected to determine the levels of reproductive hormones [estradiol (E2), luteinizing hormone (LH), and follicle stimulating hormone (FSH)]; and thyroid hormones [triiodothyronine (T3) and thyroxin (T4)]. Also, autoimmune thyroid antibodies assessment h
... Show MorePregnancy and childbirth are physiological states characterized by sudden hormonal and immunologically described changes. The current study aimed to investigate the influence of maternal variables (age, previous abortion, placental position, and fetal position) on some physiological biomarkers, such as oxytocin (OT), prolactin (PRL), cortisol, and insulin growth factor 2 (IGF -2) and some immune biomarkers such as programmed cell death protein 1 (PD-1), programmed cell death ligand 1 (PD-L1) and interleukin 6 (IL-6) in Iraqi women undergoing caesarean section (CS). Blood samples were collected from 48 pregnant women in the age range (16-43 years) and serum was obtained to determine the levels of the above biomarkers. The effect of
... Show MoreThe most common nosocomial fungal infection in hospitals is urinary tract candidiasis. Candida albicans is the most prevalent cause of nosocomial fungal urinary tract infections, however Candida species distribution is changing rapidly. At the same time, the rise in urinary tract candidiasis has resulted in the emergence of antifungal-resistant Candida species. This study aimed to diagnose Candida Spp. In women with UTI and reveal the nucleotides sequences of CA-INT-L Gene to look for mutation within the gene. This study included 100 women patients suffering from urinary tract infections and vaginal swabs samples from those individuals were taken to identify the presence of Candida. They were between the ages of 22 and 67. Candida i
... Show MoreA case-control study was designed to find out the association between rs2234671 polymorphism of cxcr1 and rUTI in a sample of Iraqi women by polymerase chain reaction- sequence-specific primer (PCR-SSP) method. The current findings revealed that the genotype GC (OR= 7.86, 95% CI = 2.82-21.87, P= 7.7 × 10-5) and the C allele (OR= 3.93, 95% CI = 1.97 - 7.83, P = 9.8×10-5) are significantly associated with rUTI. However, the genotype GG played as a protective factor (OR= 0.12, 95% CI = 10.05 - 0.34, P = 4.0 ×10-5). Depending on these findings, the genotype GC is significantly associated with rUTI.
Introduction and Aim: Diabetes mellitus patients almost always struggle with a metabolic condition known as chronic hyperglycemia. According to the World Health Organization, osteoporosis is a progressive systemic skeletal disorder that is characterized by decreasing bone mass and microstructural breakdown of bone tissue that increases susceptibility to fracture and increased risk of breaking a bone. Here, we aimed to compare the levels of CatK and total oxidative state in patients with diabetes and osteoporosis among the female Iraqi population and study the possible relationship between them. Materials and Methods: This study included 40 females with diabetes (Group G1), 40 with diabetes and osteoporosis (Group G2) and 40 normal healthy f
... Show MoreBackground: Polycystic ovary syndrome (PCOS) has an unknown and complex etiology. It affects 5–10% of women in the reproductive age. Patients are known to have increased ovarian androgen production that is associated with decreased menses, hirsutism, and acne. Urinary tract stones (UTS) are a multifactorial disorder, with age and sex being known risk factors. Many PCOS patients are obese, and links between nephrolithiasis and obesity have been shown previously. Objectives: To identify the relation between PCOS and UTS considering the patients' body mass index (BMI). Methods: This is a cross-sectional study that enrolled 407 women aged 18-40 who attended the gynecology and obstetrics clinic at Al-Elwiya Maternity Teaching Hospital.
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