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.
This study was done to compare the morphometric parameters of placentas in well controlled patients with preeclampsia, diabetes, and preeclampsia-diabetes with that of normal uncomplicated placentas. Patients & Methods: A total of Twenty four placentas were freshly collected. Six placentas for control group and eighteen placentas for complicated group (preeclamptic-diabetic and preeclamptic--diabetic subgroups). The placentas were grossly examined (shape, number of cotyledons, weight, and thickness). After suitable fixation, tissue processing and sectioning, the sections were stained by hematoxylin and eosin to study the general morphology and morphometry of the following parameters: number of terminal villi, number of syncytial knots, numb
... Show MoreThe prevalence of diabetes is increasing rapidly and is now recognized as a significant global health problem. Diabetes occurs when a person does not produce enough insulin due to an imbalance in insulin production. This can lead to the failure of organs and tissues such as the kidneys, heart, blood vessels, eyes, nerves, and kidneys. As a result, early diagnosis and classification of type 2 diabetes mellitus (T2DM) are critical to aiding physician assessments. Subsequently, the current study aims to determine irisin levels in patients with T2DM and pre-DM as early predictors for disease cases. The current study included 138 subjects divided into three groups based on fasting blood glucose (FBG) and glycosylated hemoglobi
... Show MoreThe purpose of this research is to identify the effect of the use of project-based learning in the development of intensive reading skills at middle school students. The experimental design was chosen from one group to suit the nature of the research and its objectives. The research group consisted of 35 students. For the purpose of the research, the following materials and tools were prepared: (List of intensive reading skills, intensive reading skills test, teacher's guide, student book). The results of the study showed that there were statistically significant differences at (0.05) in favor of the post-test performance of intensive reading skills. The statistical analysis also showed that the project-based learning approach has a high
... Show MoreAn essential element in English as a foreign language (EFL) learning is vocabulary. There is a big emphasis on learning the new words' meaning from the books or inside classrooms. Also, it is a major part of language teaching as well as being fundamental to the learner but there is a big challenge in vocabulary instruction due to the weak confidence by teachers in selecting the suitable practice in teaching vocabulary or they sometimes unable to specify a suitable time for it during the teaching process. The major aim of this study is to investigate the value of posters in vocabulary learning on the 2nd grade students at Halemat Alsaadia High School in Baghdad – Iraq. It hypothesized that there are no statistically significant differences
... Show MoreGestational diabetes mellitus (GDM) is a complication of gestation that is characterized by impaired glucose tolerance with first recognition during gestation. It develops when ?- cell of pancreas fail to compensate the diminished insulin sensitivity during gestation. This study aims to investigate the relationship between mother adiponectin level and ?- cell dysfunction with development gestational diabetes mellitus (GDM) and other parameters in the last trimester of pregnancy. This study includes (80) subjects ( pregnant women) in the third trimester of pregnancy, (40) healthy pregnant individuals as control group aged between (17 - 42) years and (40) gestational diabetes mellitus patients with aged between (20 - 42) years. The f
... Show MoreIn the last few years, the use of artificial neural network analysis has increased, particularly, in geotechnical engineering problems and has demonstrated some success. In this research, artificial neural network analysis endeavors to predict the relationship between physical and mechanical properties of Baghdad soil by making different trials between standard penetration test, liquid limit, plastic limit, plasticity index, cohesion, angle of internal friction, and bearing capacity. The analysis revealed that the changes in natural water content and plastic limit have a great effect on the cohesion of soil and the angle of internal friction, respectively. . On the other hand, the liquid limit has a great impact on the bearing capacity and
... Show MoreIn the present investigation, bed porosity and solid holdup in viscous three-phase inverse fluidized bed (TPIFB) are determined for aqueous solutions of carboxy methyl cellulose (CMC) system using polyethylene and polypropylene as a particles with low-density and diameter (5 mm) in a (9.2 cm) inner diameter with height (200 cm) of vertical perspex column. The effectiveness of gas velocity Ug , liquid velocity UL, liquid viscosity μL, and particle density ρs on bed porosity BP and solid holdups εg were determined. The bed porosity increases with "increasing gas velocity", "liquid velocity", and "liquid viscosity". Solid holdup decreases with increasing gas, liquid
... Show MoreThe Iraqi marshes are considered the most extensive wetland ecosystem in the Middle East and are located in the middle and lower basin of the Tigris and Euphrates Rivers which create a wetlands network and comprise some shallow freshwater lakes that seasonally swamped floodplains. Al-Hawizeh marsh is a major marsh located east of Tigris River south of Iraq. This study aims to assess water quality through water quality index (WQI) and predict Total Dissolved Solids (TDS) concentrations in Al-Hawizeh marsh based on artificial neural network (ANN). Results showed that the WQI was more than 300 for years 2013 and 2014 (Water is unsuitable for drinking) and decreased within the range 200-300 in years 2015 and 2016 (Very poor water). The develope
... Show MoreIn the last few years, the use of artificial neural network analysis has increased, particularly, in geotechnical engineering problems and has demonstrated some success. In this research, artificial neural network analysis endeavors to predict the relationship between physical and mechanical properties of Baghdad soil by making different trials between standard penetration test, liquid limit, plastic limit, plasticity index, cohesion, angle of internal friction, and bearing capacity. The analysis revealed that the changes in natural water content and plastic limit have a great effect on the cohesion of soil and the angle of internal friction, respectively. . On the other hand, the liquid limit has a great impact on the bearing capacity and
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