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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 Dec 01 2024
Journal Name
Baghdad Science Journal
Densenet Model for Binary Glaucoma Classification Performance Assessment with Texture Feature
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تعتبر شبكية العين جزءًا مهمًا من العين لأن الأطباء يستخدمون صورها لتشخيص العديد من أمراض العيون مثل الجلوكوما واعتلال الشبكية السكري وإعتام عدسة العين. في الواقع، يعد تصوير الشبكية المجزأ أداة قوية للكشف عن النمو غير العادي في منطقة العين بالإضافة إلى تحديد حجم وبنية القرص البصري. يمكن أن يؤدي الجلوكوما إلى إتلاف القرص البصري، مما يغير مظهر القرص البصري للعين. تعمل تقنيتنا على الكشف عن الجلوكوما وتصنيفه

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Publication Date
Mon Jan 01 2024
Journal Name
Bio Web Of Conferences
Concepts of statistical learning and classification in machine learning: An overview
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Statistical learning theory serves as the foundational bedrock of Machine learning (ML), which in turn represents the backbone of artificial intelligence, ushering in innovative solutions for real-world challenges. Its origins can be linked to the point where statistics and the field of computing meet, evolving into a distinct scientific discipline. Machine learning can be distinguished by its fundamental branches, encompassing supervised learning, unsupervised learning, semi-supervised learning, and reinforcement learning. Within this tapestry, supervised learning takes center stage, divided in two fundamental forms: classification and regression. Regression is tailored for continuous outcomes, while classification specializes in c

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Publication Date
Sat Jul 27 2024
Journal Name
International Journal Of Medical Science And Dental Health
The relationship between Fatty Acids and Type II Diabetes Mellitus
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We can summarize the main risk factors for type 2 diabetes mellitus (T2DM) by looking at our nutrition, age, and lifestyle. β-cell dysfunction and insulin resistance (IR) are outcomes of the pathophysiology of type 2 diabetes. As an indirect result of IR on important metabolic enzymes, lipid and lipoprotein abnormalities are also a factor in T2DM patients. Recent research has indicated that lipid fluctuation may be the cause of poor glucose metabolism as well as one of its effects. Fatty acids (FAs) affect cell membrane fluidity and permeability, insulin receptor binding and signaling, and the translocation of glucose transporters. Therefore, it is suggested that FAs might play a crucial part in the emergence of IR and T2DM.

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Publication Date
Wed Mar 11 2020
Journal Name
Journal Of Cardiovascular Disease Research
Resistive Index is an Early Indicator for Flow Deterioration in Comparison with Intima Media Thickness for Patients with Hypertension and Diabetes in Relation to Age
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Background: Atherosclerosis is well known related to age and certain cardiovascular diseases. Aging is one reason of arteries function deterioration which can cause loss of compliance and plaque accumulation, this effect increases by the presence of certain diseases such as hypertension and diabetes disease. Aim: To investigate the reduction of blood supply to the brain in patients with diabetes and hypertension with age and the role of resistive index in the diagnosis of reduced blood flow. Method: Patients with both diseases diabetic and hypertension were classified according to their age to identify the progression of the disease and factors influencing the carotid artery blood flow. By using ultrasound and standard Doppler techniq

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Publication Date
Sat Apr 15 2023
Journal Name
Journal Of Robotics
A New Proposed Hybrid Learning Approach with Features for Extraction of Image Classification
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Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

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Publication Date
Sun Jun 30 2013
Journal Name
Al-kindy College Medical Journal
Evaluation of Etiological Causes of Hypothyroidism among Patients Visiting Specialized Center for Diabetes and Endocrinology
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Background: Many structural or functional abnormalities can impair the production of thyroid hormones and cause hypothyroidism.Objectives: to identify the main etiological causes of hypothyroidism among patients visiting Specialized Center for Diabetes and Endocrinology.Methods: This study was conducted in the Specialized Center for Diabetes and Endocrinology on 217 patients with proved hypothyroidism, from 2006 to 2008. Every patient was tested with thyroid function tests, Ultrasound examination, thyroid autoantibodies, fine needle aspiration, radiology of skull, isotopes scan, also checking adrenal and gonadal function. Results: Out of these 217 patients 120 patients have thyroiditis 33 patients had been undergone thyroidectomy. 39 pat

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Publication Date
Tue Feb 17 2026
Journal Name
Sustainable Engineering And Innovation
Morlet wavelet–based olfactory-evoked EEG features for random forest classification of normal, aMCI, and Alzheimer’s disease
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Olfactory impairment and abnormal frontal EEG oscillations are recognized as early markers of Alzheimer’s disease (AD). Using a publicly available olfactory EEG dataset of 35 subjects spanning normal cognition, amnestic mild cognitive impairment (aMCI), and AD, each with MMSE scores and demographics, stimulus-locked epochs from four electrodes (Fp1, Fz, Cz, Pz) were processed with wavelet-based time–frequency analysis. Band-limited power ratios (delta, theta, alpha, beta) were computed as log-transformed post-odor/baseline values and aggregated to subject-level features. Statistical analyses revealed graded attenuation of odor-evoked frontal (Fp1) band-power ratios across groups, with significant differences in several band–od

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Publication Date
Thu Mar 01 2012
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
The role of Cost awareness of activation of strategic cost management techniques of industrial units: A prospective study at the General Company for the manufacture of medicines and medical supplies in the province of Mosul
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The last ten years observed a shift enormous scientific in the method and way that it deals professional with the cost accounting and reflected the result those shift enormous scientific of increase the competitive environmental that accompanied the emergence of a modern manufacturing environmental on surface the long roductive life and emergence advanced information technology that give a central focus of his important on client with growing global markets growth on a large scale.

        The research aim to define the concept of cost awareness, the concept and methods of  strategic cost management and the role of cost awareness for managers of industrial units in strategic of cost managem

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Publication Date
Mon Jul 04 2022
Journal Name
Indian Journal Of Forensic Medicine & Toxicology
The Correlation between Insulin Resistance and Urotensin II in Patients with Gestational Diabetes Mellitus
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Gestational diabetes mellitus is glucose intolerance of varying degree with onset or first detection duringpregnancy,it can causelong and short term morbidities in both the mother and the child, such as shoulder dystocia,preeclampsia, and high blood pressure. The most powerful endogenous vasoconstrictor peptide, urotensin II, andits receptor are involved in the etiology of gestational diabetes mellitus.Aim of the study: The study’s goal was to see if there is a link between Urotensin II levels and insulin resistancein pregnant women with gestational diabetes.Patients and method: A case-control study that was conducted in obstetrics and gynecology department atBaghdad Teaching hospital from the first of January 2019 to the end of D

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Publication Date
Sat Dec 30 2023
Journal Name
Al-kindy College Medical Journal
Assessment of Serum Metalloendopeptidase level in Patients with Double Diabetes
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Background: Double diabetes is the term used to describe situations in which a patient exhibits characteristics that are a combination of type 1 and type 2 Diabetes Mellitus. Metalloendopeptidase or Neprilysin is membrane-bound metallopeptidase. It has a wide range of physiological function and a variety of substrates. It has a significant impact on the proteolytic functions of the kidney, cardiovascular health, immunological response, cell proliferation, and fetal development. It also has a preventative effect on the onset of type 2 diabetes, obesity, and cancer.

Objective: The study aims to assess the level of MEP in patients wi

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