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.
Polycystic ovarian syndrome (PCOS) is a well-known endocrinopathy and one of the most frequent endocrine-reproductive-metabolic syndromes in women, which can result in reduced fertility. While the actual cause is unknown, PCOS is regarded as a complicated genetic characteristic with a great degree of variability. Moreover, hormones and immune cells, including both innate and acquired immune cells, are thought to interact in PCOS. Chronic low-grade inflammation raises the risk of autoimmune disease. The study's purpose is to investigate the chemokine monocyte chemoattractant protein-1 (MCP-1) and fertility hormones in samples of women patients with polycystic ovary syndrome (PCOS) in the City of Medicine. Sixty PCOS women comprise 30 heal
... Show More The main objective of this study would be that if serum lipocalin-2 and Vaspin levels may be utilized as indicators for chronic in Type 2 diabetes mellitus (T2DM) patients. T2DM treatment is to maintain a healthy glycemic level. If this goal is not met, diabetes consequences, both acute and chronic, may emerge, one of which is obesity. As a result, researchers have investigated the levels of Lipocalin-2 and Vaspin, as well as their connection to obesity and insulin resistance. In this study, we included 60 T2DM (ages 35 to 65 years) and 30 healthy controls. After an overnight fast, blood serum samples were collected, and routine biochemical parameters such as lipocalin-2, Vaspin, and glucose were measured in all samples. At a
A 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.
By measuring Adropin, fasting blood glucose (FBG), cholesterol, high-density lipoprotein (HDL), triglycerides (TG), low-density lipoprotein (LDL), and very low-density lipoprotein (VLDL) in the sera of Iraqi patients with MetS and type 2 diabetes mellitus (T2DM), the current study was designed to compare some crucial markers in metabolic syndrome (MetS) sera and diabetic patients (T2DM) with control. Twenty female subjects were divided into three groups: group I=40 with MetS and group II=40 with T2DM, and 40 healthy subjects were employed as a control group. Compared to the control group, Adropin levels in the Mets group and T2DM group decreased significantly (p < 0.05). In contrast, none of the patient groups (MetS and T2DM)
... Show MoreUltrasound has been used as a diagnostic modality for many intraocular diseases, due its safety, low cost, real time and wide availability. Unfortunately, ultrasound images suffer from speckle artifact that are tissue dependent. In this work, we will offer a method to reduce speckle noise and improve ultrasound image to raise the human diagnostic performance. This method combined undecimated wavelet transform with a wavelet coefficient mapping function: where UDWT used to eliminate the noise and a wavelet coefficient mapping function used to enhance the contrast of denoised images obtained from the first component. This methods can be used not only as a means for improving visual quality of medical images but also as a preprocessing
... Show MoreThe core objective of this paper was to diagnosis and detect the expected rotor faults in small wind turbine SWT utilize signal processing technique. This aim was achieved by acquired and analyzed the current signal of SWT motor and employed the motor current signature analysis MCSA to detect the sudden changes can have occurred during SWT operation. LabVIEW program as a virtual instrument and (NI USB 6259) DAQ were take advantage of current measurement and data processing.
Face recognition system is the most widely used application in the field of security and especially in border control. This system may be exposed to direct or indirect attacks through the use of face morphing attacks (FMAs). Face morphing attacks is the process of producing a passport photo resulting from a mixture of two images, one of which is for an ordinary person and the other is a judicially required. In this case, a face recognition system may allow travel of persons not permitted to travel through face morphing image in a Machine-Readable Electronic Travel Document (eMRTD) or electronic passport at Automatic Border Control (ABC) gates. In creating an electronic passport, most countries rely on applicant to submit ima
... Show MoreThe aim of our study is to solve a nonlinear epidemic model, which is the COVID-19 epidemic model in Iraq, through the application of initial value problems in the current study. The model has been presented as a system of ordinary differential equations that has parameters that change with time. Two numerical simulation methods are proposed to solve this model as suitable methods for solving systems whose coefficients change over time. These methods are the Mean Monte Carlo Runge-Kutta method (MMC_RK) and the Mean Latin Hypercube Runge-Kutta method (MLH_RK). The results of numerical simulation methods are compared with the results of the numerical Runge-Kutta 4th order method (RK4) from 2021 to 2025 using the absolute error, which prove
... Show MoreThe unconventional techniques called “the quick look techniques”, have been developed to present well log data calculations, so that they may be scanned easily to identify the zones that warrant a more detailed analysis, these techniques have been generated by service companies at the well site which are among the useful, they provide the elements of information needed for making decisions quickly when time is of essence. The techniques used in this paper are:
- Apparent resistivity Rwa
- Rxo /Rt
The above two methods had been used to evaluate Nasiriyah oil field formations (well-NS-3) to discover the hydrocarbon bearing formations. A compu
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