Diabetes imposes a substantial public health burden; according to the International Diabetes Federation, there were about 3.4 million diabetes related deaths worldwide in 2024, and in Iraq, the Federation reports that one in nine adults lives with diabetes in 2024, with 14,683 adult deaths attributable to diabetes and a total diabetes related health expenditure of 2,078 million United States dollars. The dataset analyzed in this study contains 1,000 records collected in 2020 from two Iraqi teaching hospitals and includes multiple clinical and laboratory measurements with three outcome classes, namely Non diabetic, Pre diabetic, and Diabetic, with a low prevalence of the Pre diabetic class and an imbalanced overall class distribution; the data are challenging because they contain many outliers, non homogeneous covariance matrices across classes, exact duplicate rows that were removed before modelling, and linear correlations among certain variables. The study objective was to train and evaluate models that discriminate among the three classes and yield accurate, well calibrated predictions for future cases in similar clinical settings, but the diagnostic properties of the data limited the applicability of classical discriminant functions; therefore two supervised learners were employed: Classification and Regression Trees (CART) and Extreme Gradient Boosting (XGBoost), together with preprocessing that removed exact duplicate rows and excluded VLDL because it is algebraically derived from triglycerides in mmol per liter as VLDL equals triglycerides divided by 2.2, which would introduce redundancy and multicollinearity. On the heldout test set, XGBoost achieved higher Accuracy at 98.18 percent compared with 97.58 percent for CART and higher Balanced Accuracy at 93.84 percent compared with 88.16 percent for CART, indicating that XGBoost provided the strongest overall operating point for this three-class task while CART remains useful when simple and transparent rules are required.
As material flow cost accounting technology focuses on the most efficient use of resources like energy and materials while minimizing negative environmental effects, the research aims to show how this technology can be applied to promote green productivity and its reflection in attaining sustainable development. In addition to studying sustainability, which helps to reduce environmental impacts and increase green productivity, the research aims to demonstrate the knowledge bases for accounting for the costs of material flow and green productivity. It also studies the technology of accounting for the costs of material flow in achieving sustainable development and the role of green productivity in achieving sustainable development. According
... Show MoreIn Iraq, more than 1031 school projects have been halted due to disputes and claims resulting from financial, contractual, or other issues. This research aims to identify, prioritize, and allocate the most critical risk factors that threaten these projects’ success for the duration (2017-2022). Based on a multi-step methodology developed through systematic literature reviews, realistic case studies, and semi-structured interviews, 47 risk factors were identified. Based on 153 verified responses, the survey reveals that the top-ranked risk factors are corruption and bribery, delaying the payments of the financial dues to the contractors or sub-contractors, absence of risk management strategy, multiple change orders due
... Show More
Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an ob
... Show MoreCodes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an object under de
... Show MoreThis study focusses on the effect of using ICA transform on the classification accuracy of satellite images using the maximum likelihood classifier. The study area represents an agricultural area north of the capital Baghdad - Iraq, as it was captured by the Landsat 8 satellite on 12 January 2021, where the bands of the OLI sensor were used. A field visit was made to a variety of classes that represent the landcover of the study area and the geographical location of these classes was recorded. Gaussian, Kurtosis, and LogCosh kernels were used to perform the ICA transform of the OLI Landsat 8 image. Different training sets were made for each of the ICA and Landsat 8 images separately that used in the classification phase, and used to calcula
... Show MoreDiabetes mellitus caused by insulin resistance is prompted by obesity. Neuropeptide Nesfatin-1 was identified in several organs, including the central nervous system and pancreatic islet cells. Nesfatin-1 peptide appears to be involved in hypothalamic circuits that energy homeostasis and control food intake. Adiponectin is a plasma collagen-like protein produced by adipocytes that have been linked to the development of insulin resistance (IR), diabetes mellitus type 2 (DMT2), and cardiovascular disease (CVD). Resistin was first identified as an adipose tissue–specific hormone that was linked to obesity and diabetes. The aim of this study was to estimate the relationship between human serum nesfatin-1, adiponect
... Show MoreHepatitis is one of the diseases that has become more developed in recent years in terms of the high number of infections. Hepatitis causes inflammation that destroys liver cells, and it occurs as a result of viruses, bacteria, blood transfusions, and others. There are five types of hepatitis viruses, which are (A, B, C, D, E) according to their severity. The disease varies by type. Accurate and early diagnosis is the best way to prevent disease, as it allows infected people to take preventive steps so that they do not transmit the difference to other people, and diagnosis using artificial intelligence gives an accurate and rapid diagnostic result. Where the analytical method of the data relied on the radial basis network to diagnose the
... Show MoreIn this research, a group of gray texture images of the Brodatz database was studied by building the features database of the images using the gray level co-occurrence matrix (GLCM), where the distance between the pixels was one unit and for four angles (0, 45, 90, 135). The k-means classifier was used to classify the images into a group of classes, starting from two to eight classes, and for all angles used in the co-occurrence matrix. The distribution of the images on the classes was compared by comparing every two methods (projection of one class onto another where the distribution of images was uneven, with one category being the dominant one. The classification results were studied for all cases using the confusion matrix between every
... Show MoreGlutathione S-transferases (GSTs) are enzymes that included, in a more range of detoxifying reactions by conjugation of glutathione, to electrophilic material. Polymorphisms n the genes that responsible of GSTs affect, the function of the GSTs. GSTs play an active role in protection of cell against oxidative stress mechanism. Polymorphisms of GSTP1 at codon 105 amino acids forms GSTP1 important site for bind of hydrophobic electrophiles and the substitution of Ile/Val affect substrate specially catalytic activity of the enzyme and may correlate with reach to different diseases in human like diabetes mellitus type2 disease. Correlation between these polymorphisms and changes in the parameters file of diabetic patients has also bee
... Show More