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.
Objective: 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 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
... 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 MoreIn this study, active knife and fixed knife of single-row disc silage machine has three different clearance C1, C2 and C3 (1, 3 and 5 mm) and it is tried in three different working speed V1, V2 and V3 (1.8, 2.5 and 3.7 km / h) and PTO speed (540 min-1) and machine's fuel consumption (l/h), average power consumption (kW), field energy consumption (kW/da), product energy consumption (kW/t), field working capacity (da/h), product working capacity (t/h) and Chopping size distribution characteristics of the fragmented material were determined. It has been found that knife-counter knife clearances smaller than 3 mm (1 mm) and larger (5 mm) have a negative effect on machine performance in general. In terms of fuel and power consumptions, the m
... Show MoreObjective: study aims to identify the diabetes type2 clients self management skills toward dietary pattern
, and find out the relationship between variables which are (Age, gender, educational level, duration of DM
diagnosis, and monthly income) with diabetes type 2 clients self management skills toward dietary pattern
Methodology: descriptive study was carried out through the present investigation from January 2nd
2011to September 2nd 2011 in order to achieve the objectives of the present study. A non probability
(purposive) sample, (200) cases which consists of clients who were attending Al-Nasiriyha diabetic center.
Including (118) males and (82) females. The data were collected by utilization of the study instrument
Aspartate aminotransferase was purified from urine and serum of patients with type 2 diabetes in a 2 steps procedure involving dialysis bag and sephadex G-25 gel filtration (column chromatography). The enzyme was purified 346.23 fold with 1467% yield and 3.46 fold with 142.85% yield in urine and serum of patients with type 2 diabetes respectively. The purified enzyme showed single peak. The results of this study revealed that AST activity of type 2 diabetes urine and serum increased significantly (p<0.001) compared with control group.
Background: Diabetes mellitus is a common health problem of the world. Iron may be a part of the cause of the disease and its Complications
Objectives: This study was designed to determine the relationship between the levels of iron indices and diabetes mellitus type 2. Type 2
Type of the study: Cross –sectional study.
Methods: diabetes mellitus is clinical condition characterized by hyperglycemia due to the absolute or relative deficiency of insulin. It is also followed by pathological abnormalities like impaired insulin secretion, peripheral insulin resistance, and excessive hepatic glucose production. Although type 2 diabetes mellitus i
... Show MoreThe glycated haemoglobin A1c(HbA1c) and Fasting blood glucose(FBG) effect on type1 diabetic pateints as a screening tests and as a gold standard for assessing glycemic control in subjects with diabetes were studied . Ninety one blood samples were collected in a peroid between June and the end of November 2012 at AL- Kindy Diabetic Center and Central Child Hospital,48 Females and 43 Males , aging between (11 month- 18 year), are divided into three groups, newly diagnosed , ongoing and healthy control group, with duration of disease between(1 day-3months) and (from birth-8 years) for newly diag
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