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Diabetes Prediction Using Machine Learning
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Diabetes is one of the increasing chronic diseases, affecting millions of people around the earth. Diabetes diagnosis, its prediction, proper cure, and management are compulsory. Machine learning-based prediction techniques for diabetes data analysis can help in the early detection and prediction of the disease and its consequences such as hypo/hyperglycemia. In this paper, we explored the diabetes dataset collected from the medical records of one thousand Iraqi patients. We applied three classifiers, the multilayer perceptron, the KNN and the Random Forest. We involved two experiments: the first experiment used all 12 features of the dataset. The Random Forest outperforms others with 98.8% accuracy. The second experiment used only five attributes of the training process. The results of the second experiment showed improvement in the performance of the KNN and the Multilayer Perceptron. The results of the second experiment showed a slight decrease in the performance of the Random Forest with 97.5 % accuracy.

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Publication Date
Sun Oct 01 2023
Journal Name
Baghdad Science Journal
Synthesis, characterization, molecular docking, ADMET prediction, and anti-inflammatory activity of some Schiff bases derived from salicylaldehyde as a potential cyclooxygenase inhibitor
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A series of Schiff base-bearing salicylaldehyde moiety compounds (1-4) had been designed, synthesized, subjected to insilico ADMET prediction, molecular docking, characterization by FT-IR, and CHNS analysis techniques, and finally to their Anti-inflammatory profile using cyclooxygenase fluorescence inhibitor screening assay methods along with standard drugs, celecoxib, and diclofenac. The ADMET studies were used to predict which compounds would be suitable for oral administration, as well as absorption sites, bioavailability, TPSA, and drug likeness. According to the results of ADME data, all of the produced chemicals can be absorbed through the GIT and have passed Lipinski’s rule of five. Through molecular docking with PyRx 0.8, these

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Publication Date
Fri Dec 23 2022
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Descriptive, Prospective Observational Study- Studying Possible Prediction Factors for Disease Severity and Progression among a Sample of COVD 19 Patients in Iraq
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Abstract

Coronavirus has affected many people around the world and caused an increase in the number of hospitalized patients and deaths. The prediction factor may help the physician to classify whether the patient needs more medical attention to decrease mortality and worsening of symptoms. We aimed to study the possible relationship between C reactive protein level and the severity of symptoms and its effect on the prognosis of the disease. And determine patients who require closer respiratory monitoring and more aggressive supportive therapies to avoid poor prognosis. The data was gathered using medical record data, the patient's medical history, and the onset of symptoms, as well as a blood sample to test the

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Publication Date
Wed Jul 13 2022
Journal Name
International Journal Of Health Sciences
Study of the reliability of serum vascular endothelial growth factor and its soluble receptor as markers of diabetic nephropathy in type 2 diabetes patients
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The levels of circulating angiogenic and anti-angiogenic factors, namely vascular endothelial growth factor–A (VEGF-A) and soluble vascular endothelial growth factor receptor-1 (sVEGFR-1), have been linked to the development of renal dysfunction due to the proliferation of microvasculature within the kidneys of type 2 diabetic (T2DM) patients. The study aims to scrutinize serum levels of VEGF and sVEGFR-1 in a sample of Iraqi diabetic nephropathy patients to support their reliability as markers for the prediction of nephropathy in type 2 diabetes mellitus patients as well as to assess the ACE inhibitor’s effect on the levels of these two markers. Method: The ninety participants of this case-control study were split into three gr

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Publication Date
Thu Apr 27 2023
Journal Name
Journal Of The Faculty Of Medicine Baghdad
Evaluation of the Effect of Type II Diabetes mellitus on Bone Mineral Density of Upper and Lower Limbs by Dual-Energy X-Ray Absorptiometry
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Background: Bone mineral density has been assessed using Dual-Energy X-Ray Absorptiometry. Bone mineral density is measured according to the results of the Dual-Energy X-Ray Absorptiometry examination of the vertebral column and pelvis. Although diabetes mellitus type II (DM) is known to affect bone mineral density, at the present time this particular relationship is not clear. Objective: The aim of current study was to evaluate the effects of type II diabetes mellitus on bone mineral density of the upper and lower limbs as well as gender differences. Patients and Methods: This study involved 165 patients complaining of bone pain (85 males and 80 females), 85 patients of who suffered from diabetes, involving both genders. In addition,

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Publication Date
Tue Jan 01 2019
Journal Name
Iraqi Journal Of Agricultural Sciences
Role of calcium-regulating hormones, adipocytokines and renal function test in the progress of type 2 diabetes mellitus in a sample of Iraqi patients
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A cross-sectional study was conducted on 80 type 2 diabetic patients aged 20-60 years in Baghdad and 20 non diabetic persons as controls. Laboratory assessment of glucose related parameters; Fasting blood sugar (FBS), Glycated hemoglobin (HbA1c), Insulin and Insulin resistance (IR), renal function test; Blood urea, serum creatinine, Calcium (Ca) and Phosphorus (P), Calcium regulating hormones; Parathyroid hormone (PTH), calcitonin and vitamin D, cytokines, Adiponectin and Tumor necrosis factor (TNF-α) and comparison these parameters between patients and controls. The results: a high significant (p˂0.01) increase in FBG level in the patients (211.34 ± 11.20 mg/dl) as compared with control (85.89 ± 3.07 mg/dl). A high significant (p˂0.01

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Publication Date
Tue Jan 20 2026
Journal Name
Journal Mustansiriyah Of Sports Science
The influence of excellent offensive basketball skill-learning activities based on sensory perceptions for female pupils.
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The aim of this research is to develop qualitative workouts based on certain sensory perceptions for the development of offensive basketball abilities and to determine their impact on female pupils. Several findings, based on the au-thor's extensive expertise instructing basketball materials and our closeness to the sample, revealed deficits in some sensory perceptions “in the game of basketball”, which impair the accuracy of passing the ball to the best team-mate. It also affects the pace of dribbling and the difficulty of selecting the op-timal moment and distance to fire. Therefore, the researcher designs qualita-tive activities based on many sensory experiences, including distance, speed, force, and direction shift. In addition, the

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Publication Date
Tue Jun 01 2021
Journal Name
Al-khwarizmi Engineering Journal
Effect of Environmental Factors on the Accuracy of a Quality Inspection System Based on Transfer Learning
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In this research, a study is introduced on the effect of several environmental factors on the performance of an already constructed quality inspection system, which was designed using a transfer learning approach based on convolutional neural networks. The system comprised two sets of layers, transferred layers set from an already trained model (DenseNet121) and a custom classification layers set. It was designed to discriminate between damaged and undamaged helical gears according to the configuration of the gear regardless to its dimensions, and the model showed good performance discriminating between the two products at ideal conditions of high-resolution images. So, this study aimed at testing the system performance at poo

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Publication Date
Sun Sep 06 2020
Journal Name
European Journal Of Dental Education
Evaluation of technology‐based learning by dental students during the pandemic outbreak of coronavirus disease 2019
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Publication Date
Tue Jun 01 2021
Journal Name
Al-khwarizmi Engineering Journal
Effect of Environmental Factors on the Accuracy of a Quality Inspection System Based on Transfer Learning
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In this research, a study is introduced on the effect of several environmental factors on the performance of an already constructed quality inspection system, which was designed using a transfer learning approach based on convolutional neural networks. The system comprised two sets of layers, transferred layers set from an already trained model (DenseNet121) and a custom classification layers set. It was designed to discriminate between damaged and undamaged helical gears according to the configuration of the gear regardless to its dimensions, and the model showed good performance discriminating between the two products at ideal conditions of high-resolution images.

So, this study aimed at testing the system performance at poor s

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Publication Date
Fri Apr 14 2023
Journal Name
Journal Of Big Data
A survey on deep learning tools dealing with data scarcity: definitions, challenges, solutions, tips, and applications
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Abstract<p>Data scarcity is a major challenge when training deep learning (DL) models. DL demands a large amount of data to achieve exceptional performance. Unfortunately, many applications have small or inadequate data to train DL frameworks. Usually, manual labeling is needed to provide labeled data, which typically involves human annotators with a vast background of knowledge. This annotation process is costly, time-consuming, and error-prone. Usually, every DL framework is fed by a significant amount of labeled data to automatically learn representations. Ultimately, a larger amount of data would generate a better DL model and its performance is also application dependent. This issue is the main barrier for</p> ... Show More
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