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XGBOOST AND COST-SENSITIVE CART FOR IMBALANCED MULTICLASS DIABETES CLASSIFICATION IN IRAQ
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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.

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Publication Date
Sun Jan 01 2023
Journal Name
Medical Journal Of Babylon
Evaluation of the Salivary Levels of Interleukin-17 and Galectin-3 in Patients with Periodontitis and Type 2 Diabetes Mellitus
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Background: Periodontitis and type 2 diabetes mellitus are both considered as a chronic disease that affect many people and have an interrelationship in their pathogenesis. Objective: The aim is to evaluate the salivary levels of interleukin-17 (IL-17) and galectin-3 in patients with periodontitis and type-2 diabetes mellitus. Materials and Methods: The samples were gathered from 13 healthy (control group) and 75 patients split into 3 groups, 25 patients with type 2 diabetes mellitus and healthy periodontium (T2DM group), 25 patients with generalized periodontitis (P group), and 25 patients with generalized periodontitis and type 2 diabetes mellitus (P-T2DM group). Clinical periodontal parameters were documented. The concentration of IL-17

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Publication Date
Wed Jun 10 2026
Journal Name
Journal Of Baghdad College Of Dentistry
Salivary α-Amylase and Albumin Levels in Patients with Chronic Periodontitis and Poorly or Well Controlled Type II Diabetes Mellitus
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Background: Recent studies suggest that chronic periodontitis (CP) and type2 diabetes mellitus (T2DM) are bidirectionally associated. Analysis of saliva as a mirror of oral and systemic health could allow identification of α amylase (α-Am) and albumin (A1) antioxidant system markers to assist in the diagnosis and monitoring of both diseases. The present study aims at comparing the clinical periodontal parameters in chronic periodontitis patients with poorly or well controlled Type 2Diabetes Mellitus, salivary α-Am, A1, flow rate (FR) and pH then correlate between biochemical, physical and clinical periodontal parameters of each study and control groups. Materials and Methods: 80 males, with an age range of (35-50) years were divide

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Publication Date
Tue Feb 01 2022
Journal Name
Baghdad Science Journal
Association of Endothelin-I and A symmetric Dimethylarginine Levels with Insulin Resistance in Type-2 Diabetes Mellitus Patients
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Endothelin-I (ET-I) is one of the potent vasoconstrictors secreted from endothelial cells when needed. Many studies revealed the elevation of serum ET-I with human diabetes and microangiopathies. Since insulin resistance is a case of mixed diabetic and pre-diabetic cases, many risk factors beyond obesity and inflammation are proposed. The current study aims to demonstrate the association between serum ET-I and asymmetric dimethylarginine (ADMA) and insulin resistance in type 2 diabetes mellitus (T2DM). Sera of 73 subjects were enrolled currently (control= 35 subjects, and 38 with T2DM for more than 7 years), aged (40-60) years old, with distinct body mass index (BMI) ≤ 25 for control volunteers and (BMI) ≥ 25 for obesity and diabetes

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Publication Date
Thu Oct 20 2022
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
A study of Hepcidin levels and other Biochemical parameters in woman with Osteoporosis with Type 2 Diabetes Mellitus
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Background: Diabetes mellitus (DM) could be regarded as a set of chronic metabolic disorders which have a common aspect of hyperglycemia. The resistance in the peripheral actions of insulin or impaired insulin secretion could be the reason  hepcidin which is a peptide hormone derived from liver, in systemic iron homeostasis is an essential regulator, and its lopsided production participates in the pathogenesis of iron disorders in spectrum. Osteoporosis often accompanies many diseases like ß-thalassemia, hemochromatosis, sickle liver diseases, cell disease and hemosiderosis featured by iron overload, evidences suggest that Iron overload and iron deficiency are suggested by evidences that they affect bone in a negative way, acting

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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
Oil spill classification based on satellite image using deep learning techniques
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 An oil spill is a leakage of pipelines, vessels, oil rigs, or tankers that leads to the release of petroleum products into the marine environment or on land that happened naturally or due to human action, which resulted in severe damages and financial loss. Satellite imagery is one of the powerful tools currently utilized for capturing and getting vital information from the Earth's surface. But the complexity and the vast amount of data make it challenging and time-consuming for humans to process. However, with the advancement of deep learning techniques, the processes are now computerized for finding vital information using real-time satellite images. This paper applied three deep-learning algorithms for satellite image classification

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Publication Date
Sat Sep 11 2010
Journal Name
Journal Of Al-nahrain University
ESTIMATION ACTIVITY OF LAP IN PATIENT S WITH TYPE 2 DIABETES BY USING LEUCINE AMIDE AS SUBSTRATE
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This study was performd on 50 serum specimens of patients with type 2 diabetes, in addition, 50 normal specimens were investigated as control group. The activity rate of LAP in patients (560.46 10.504) I.U/L and activity rate of LAP in healthy(10.58 4.39)I.U/L.The results of the study reveal that Leucine aminopeptidase (LAP) activity of type 2 diabetes patient s serum shows a high signifiacant increase (p < 0.001) compare to healthy subjects. Addition preparation leucine amide as substrate of LAP, identification melting point and spectra by FTIR. K

Publication Date
Sun Feb 17 2019
Journal Name
Iraqi Journal Of Physics
Classification of the galaxy Milky Way using variable precision rough sets technique
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Astronomy image is regarded main source of information to discover outer space, therefore to know the basic contain for galaxy (Milky way), it was classified using Variable Precision Rough Sets technique to determine the different region within galaxy according different color in the image. From classified image we can determined the percentage for each class and then what is the percentage mean. In this technique a good classified image result and faster time required to done the classification process.

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Publication Date
Sat Jul 01 2023
Journal Name
Journal Of Engineering
Develop Proactive System for Risk Management (DPSRM) for Lagging Investment Project in Iraq.
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To finalize any construction investment project, it would be necessary to identify the most significant problems and obstacles that lead to project reluctance and stalling. Unexpected events and conflicts may have disrupted these strategies and impacted project development. Due to the high initial investment costs of construction projects, crises can have an immediate impact, resulting in significant financial losses. The 2014 financial crisis was one of the most prominent crises that Iraq faced, which prompted the researcher to identify and evaluate those obstacles through this research and questionnaires using Pareto scientific theory to exclude factors that do not contribute to project lag. It was discovered that 28 o

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Publication Date
Sat Jun 01 2024
Journal Name
Journal Of Physics: Conference Series
Study of The Effect of Concentration on The Efficiency of The Sensitive N749-TiO2 Solar Cell
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In this research, we studied the effect of concentration carriers on the efficiency of the N749-TiO2 heterogeneous solar cell based on quantum electron transfer theory using a donor-acceptor scenario. The photoelectric properties of the N749-TiO2 interfaces in dye sensitized solar cells DSSCs are calculated using the J-V curves. For the 〖(CH_3)〗_3 COH solvent, the N749-TiO2 heterogeneous solar cell shows that the concentration carrier together with the strength coupling are the main factors affecting the current density, fill factor and efficiency. The current density and current increase as the concentration increases and the strength coupling increases as the N749-TiO2 heterogeneous in solar cell. However, the efficiency is more sens

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Publication Date
Fri Jan 01 2016
Journal Name
Journal Of Sensors
WDARS: A Weighted Data Aggregation Routing Strategy with Minimum Link Cost in Event-Driven WSNs
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Realizing the full potential of wireless sensor networks (WSNs) highlights many design issues, particularly the trade-offs concerning multiple conflicting improvements such as maximizing the route overlapping for efficient data aggregation and minimizing the total link cost. While the issues of data aggregation routing protocols and link cost function in a WSNs have been comprehensively considered in the literature, a trade-off improvement between these two has not yet been addressed. In this paper, a comprehensive weight for trade-off between different objectives has been employed, the so-called weighted data aggregation routing strategy (WDARS) which aims to maximize the overlap routes for efficient data aggregation and link cost

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