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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Old Iraq includes the first experiences in establishing the first residential settlements in the Mesopotamian, and model villages designed and the pulp units in it and their natural matter, that made it perennial, and construction continues until now with it. These experiences were the basis for the emergence of the Iraqi civilization and thus the world and the beginning of writing, trade and the religions of the divine since before history, and then the Sumerian, Babylonian and Assyrian civilizations, and their villages that formed the Fertile Crescent.
There is a lack of knowledge and disregard for the distant and near history of Iraq in the field of rural housing, despite Iraq's leadership in this field, with the aim of the re
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Both type 1 diabetes and type 2 diabetes have a genetic component, with over 60 chromosomal regions related to type 1 diabetes and over 200 connected with type 2 diabetes at significant genome-wide levels. Numerous single nucleotide polymorphisms in the RETN gene and genetic variables can account for up to 70% of the variations in circulating resistin levels. The RETN polymorphism has been linked in numerous studies to obesity, insulin sensitivity, type 2 diabetes, and cerebrovascular illness. Our objective is to compare this RETN gene 3ʹ-untranslated region polymorphism in type 1 diabetes and type 2 diabetes Iraqi patients. We choose 51 type 1 diabetes and 52 type 2 diabetes patients against 50 healthy subjects (control group) to investig
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To evaluate the effects of the ShotBlocker and vibration device on pain intensity and patient satisfaction during subcutaneous (SC) insulin injections in hospitalized adults with type 2 diabetes mellitus.
In this randomized controlled trial, 102 patients with type II diabetes mellitus were randomly assigned into 3 groups: 35 patients in the ShotBlocker group, 36 patients in the vibration group, and 31 patients in the control group. ShotBlocker was applied immediately before and during the injection, while the vibration was applied fo
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There are many techniques that can be used to estimate the spray quality traits such as the spray coverage, droplet density, droplet count, and droplet diameter. One of the most common techniques is to use water sensitive papers (WSP) as a spray collector on field conditions and analyzing them using several software. However, possible merger of some droplets could occur after they deposit on WSP, and this could affect the accuracy of the results. In this research, image processing technique was used for better estimation of the spray traits, and to overcome the problem of droplet merger. The droplets were classified as non-merged and merged droplets based on their roundness, then the merged droplets were separated based on the average non-m
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Background/Objectives: The purpose of this study was to classify Alzheimer’s disease (AD) patients from Normal Control (NC) patients using Magnetic Resonance Imaging (MRI). Methods/Statistical analysis: The performance evolution is carried out for 346 MR images from Alzheimer's Neuroimaging Initiative (ADNI) dataset. The classifier Deep Belief Network (DBN) is used for the function of classification. The network is trained using a sample training set, and the weights produced are then used to check the system's recognition capability. Findings: As a result, this paper presented a novel method of automated classification system for AD determination. The suggested method offers good performance of the experiments carried out show that the
... Show MoreWhenever, the Internet of Things (IoT) applications and devices increased, the capability of the its access frequently stressed. That can lead a significant bottleneck problem for network performance in different layers of an end point to end point (P2P) communication route. So, an appropriate characteristic (i.e., classification) of the time changing traffic prediction has been used to solve this issue. Nevertheless, stills remain at great an open defy. Due to of the most of the presenting solutions depend on machine learning (ML) methods, that though give high calculation cost, where they are not taking into account the fine-accurately flow classification of the IoT devices is needed. Therefore, this paper presents a new model bas
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Plane cubics curves may be classified up to isomorphism or projective equivalence. In this paper, the inequivalent elliptic cubic curves which are non-singular plane cubic curves have been classified projectively over the finite field of order nineteen, and determined if they are complete or incomplete as arcs of degree three. Also, the maximum size of a complete elliptic curve that can be constructed from each incomplete elliptic curve are given.