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.
Background: In the past, an association between Tuberculosis (TB) and Diabetes Mellitus (DM) was widely accepted, today the potential public health and clinical importance of this relationship seems to be largely ignored. The national clinical and policy guidance in the UK on the central of TB, for example, does not consider the relationship with DM.Objectives: To determine the risk of association between diabetes mellitus and pulmonary TB.Methods: A retrospective study conducted in Ibn Zuhr hospital for chest diseases from Jan 2008 – sep 2010 , included in the study 402 patients with TB divided into diabetic & non diabetic, 96 (23.8%) were diabetic while other 306 were TB not diabetic.Results: Risk of TB among DM patients were cle
... Show MoreObjectives: Teenage pregnancy with gestational diabetes mellitus (GDM) offers a real challenge to the health system and needs a special care. We aimed to evaluate possible obstetrical and neonatal adverse events of different treatment protocols in adolescent GDM including lifestyle, metformin (MTF), and insulin. Methods: All teen pregnant women ≤ 19 years old visiting Baghdad Teaching Hospital throughout four years (from June 1, 2016 till May 31, 2020) diagnosed with GDM were included in this cohort study and followed-up closely throughout pregnancy and after delivery. Included adolescents were put on lifestyle alone during the first week of presentation. Adolescents who reached target glucose measurements were categorized i
... Show MoreThe current study aims at identifying the impact of using learning acceleration model on the achievement of mathematics for third intermediategrade students. Forachieving this, the researchers chose the School (Al-Kholood Secondary School for Girls) affiliated to the General Directorate of Babylon Education / Hashemite Education Department for the academic year (2021/2021), The sample reached to (70) female students from the third intermediate grade, with (35) female students for each of the two research groups. The two researchers prepared an achievement test consisting of (25) objective items of multiple choice type, The psychometric properties of the test were confirmed, and after the completion of the experiment, the achievement test wa
... Show More<span lang="EN-US">The need for robotics systems has become an urgent necessity in various fields, especially in video surveillance and live broadcasting systems. The main goal of this work is to design and implement a rover robotic monitoring system based on raspberry pi 4 model B to control this overall system and display a live video by using a webcam (USB camera) as well as using you only look once algorithm-version five (YOLOv5) to detect, recognize and display objects in real-time. This deep learning algorithm is highly accurate and fast and is implemented by Python, OpenCV, PyTorch codes and the Context Object Detection Task (COCO) 2020 dataset. This robot can move in all directions and in different places especially in
... Show MoreObjective: To investigate the relation between dyslipidemia and insulin resistance where it is one of the metabolic
disorders in patients with type-ΙΙ diabetes mellitus and compare the results with the control group.
Methodology: Blood samples were collected from (35) patients with type-ΙΙ diabetes mellitus, besides (35) healthy
individuals as a control group were enrolled in this study. The age of all subjects range from (20-50). Serum was
used in determination of glucose, insulin, lipid profile (cholesterol (Ch), triglyceride (TG), high-density lipoprotein
(HDL-Ch), low-density lipoprotein (LDL-Ch) and very low-density lipoprotein (VLDL), for patients and control
groups. Insulin resistance (IR) was calculated acco
Reservoir permeability plays a crucial role in characterizing reservoirs and predicting the present and future production of hydrocarbon reservoirs. Data logging is a good tool for assessing the entire oil well section's continuous permeability curve. Nuclear magnetic resonance logging measurements are minimally influenced by lithology and offer significant benefits in interpreting permeability. The Schlumberger-Doll-Research model utilizes nuclear magnetic resonance logging, which accurately estimates permeability values. The approach of this investigation is to apply artificial neural networks and core data to predict permeability in wells without a nuclear magnetic resonance log. The Schlumberger-Doll-Research permeability is use
... Show MoreTo determine the relationship between hepatitis C virus infection and Diabetic mellitus type 2 , twenty patient's with diabetic mellitus type 2 aged (30-61) years old have been investigated from 01/11/2014 to 01/02/2015 and compared with fifteen parentally healthy individuals. All the studies groups were carried out to measure anti-HCV Abs by enzyme linked immunosorbent assay (ELISA), There was significant elevation (P≤0.05) in the HCV Abs compared with control groups .The percentage of HCV Abs was 15% and there was highly significant (P≤0.01) differences between studied group, while there was non-significant differences (P≥0.05) between patients groups according to age and gender compared with control groups. These results indicated
... Show MoreIn this study, the harvest of maize silage with the cross double row sowing method were tested with a single row disc silage machine in two different PTO applications (540 and 540E min-1) and at two different working speeds v1, v2 (1.8 and 2.5 km h-1). The possibilities of harvesting with a single row machine were revealed, and performance characteristics such as hourly fuel consumption, field-product fuel consumption and PTO power consumption were determined in the trials. The best results in terms of hourly fuel consumption and PTO power consumption were determined in the 540E PTO application and V1 working speed. When the fuel consumption of the field-product is evaluated, it is obtained with V2 working speed and 540E PTO application. As
... Show MoreBackground: Diabetes mellitus is a major health issue that is one of the leading causes of cardiovascular disease. Recent studies have found a link between uncontrolled diabetes and cardiovascular disease, with dyslipidaemia predicting glycated-hemoglobin (HbA1c), which could be a major contributor to type 2 diabetes complications and etiology.
Objectives: The objective of present study was estimate lipid profiles among control and uncontrolled type 2 diabetic patients.
Subjects and Methods: Analytical case control based study, One hundred twenty participate were included in study, 70 patients with DM as case group refer to Abuagala Center and difference follow up diabetic center and 50 non diabetic subjects taken as
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