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.
The objective of the present study is to compare the effect of insulin like growth factor-1 on the lipid profile in sera of diabetic patients with and without dyslipidemia having the same medical treatment and compared with healthy control. The study included three groups. The biochemical parameters which were measured include, fasting blood sugar(FBS), glycated hemoglobin (HbA1c), fasting insulin, insulin like growth factor-1(IGF-1), lipid profile [Total cholesterol (Tc) , triglyceride(TG), high density lipoprotein cholesterol(HDL-c) ,low density lipoprotein-cholesterol (LDL-c)and very low density lipoprotein-cholesterol (VLDL-c)], Atherogenic index of plasma(AIP), insulin resistance(IR). The resu
... Show MoreToxoplasmosis is the term for infection and disease in man and animal caused by a parasite called Toxoplasma gondii. The more susceptible to infect with toxoplasmosis is the Diabetic patients, due to low level of immunity response. The aim of current study is to investigate the immune status of diabetes mellitus type 2. One hundred and seventy five samples of both diabetes mellitus type 2patients and controls which had been tested by ELISA technique to detect anti-Toxoplasma Abs (IgG and IgM). The positive toxoplasmosis samples were tested to detect the level of TNF alpha and MIG. Results for all samples clarified that seronegative for IgM antibodies while 53 (53%) diabetic patients were seropositive for IgG antibodies and for toxoplasmosis
... Show MoreThere are a few studies that discuss the medical causes for diabetic foot (DF) ulcerations in Iraq, one of them in Wasit province. The aim of our study was to analyze the medical, therapeutic, and patient risk factors for developing DF ulcerations among diabetic patients in Baghdad, Iraq.
The present study was included a measurements of fasting serum glucose, total protein, potassium, and calcium levels in the sera of 25 diabetic male patients suffer from chronic renal failure; their ages range were (32-75) and compared them with 25 healthy males as control group. The aim of this study was to study the effects of antidiabetic drugs on some biochemical parameters such as fasting serum glucose, serum total protein, serum potassium and calcium. The current results demonstrated a hyperkalemia in patients and this increasing of potassium is significantly (p = 0.03), but calcium level showed no significant variations ( p>0.05 ), and serum total protein was significantly decreased in patients as compared to t
... Show MoreDiabetic foot ulcer (DFU) or Lower limb ulcers are one of the major complications caused by diabetes mellitus especially when patients fail to maintain tight glycemic control. DFU is linked to multiple risk factors along with the genetic factors and ethnicity which play a significant role in the development of DFUs through their effects on multiple aspects of the pathophysiological process. This narrative review aimed to summarize all the previous studies within the last ten years associating gene polymorphism and DFU. Polymorphism associated with vascular endothelial growth factor (rs699947), the G894T polymorphism of the endothelial nitric oxide synthase gene, interleukin-6–174 G>C gene polymorphism, heat shock protein 70 gene polymorph
... Show MoreThis paper presents a combination of enhancement techniques for fingerprint images affected by different type of noise. These techniques were applied to improve image quality and come up with an acceptable image contrast. The proposed method included five different enhancement techniques: Normalization, Histogram Equalization, Binarization, Skeletonization and Fusion. The Normalization process standardized the pixel intensity which facilitated the processing of subsequent image enhancement stages. Subsequently, the Histogram Equalization technique increased the contrast of the images. Furthermore, the Binarization and Skeletonization techniques were implemented to differentiate between the ridge and valley structures and to obtain one
... Show MoreThis study compared and classified of land use and land cover changes by using Remote Sensing (RS) and Geographic Information Systems (GIS) on two cities (Al-Saydiya city and Al-Hurriya) in Baghdad province, capital of Iraq. In this study, Landsat satellite image for 2020 were used for (Land Use/Land Cover) classification. The change in the size of the surface area of each class in the Al-Saydiya city and Al-Hurriya cities was also calculated to estimate their effect on environment. The major change identified, in the study, was in agricultural area in Al-Saydiya city compare with Al-Hurriya city in Baghdad province. The results of the research showed that the percentage of the green
Human detection represents a main problem of interest when using video based monitoring. In this paper, artificial neural networks, namely multilayer perceptron (MLP) and radial basis function (RBF) are used to detect humans among different objects in a sequence of frames (images) using classification approach. The classification used is based on the shape of the object instead of depending on the contents of the frame. Initially, background subtraction is depended to extract objects of interest from the frame, then statistical and geometric information are obtained from vertical and horizontal projections of the objects that are detected to stand for the shape of the object. Next to this step, two ty
... Show MorePurpose: to review in detail various aspects of odontogenic keratocyst, emphasizing recent nomenclature, clinical, histopathological, recurrence, and management of odontogenic keratocyst.
Methods: To achieve the objective of this review, a manual search was done in hard copy books of oral and maxillofacial pathology, and an electronic search was done in the google website, oral and maxillofacial pathology E-books, virtual database sites, such as PubMed, Research Gate, Academia, and Google scholar using the descriptors: odontogenic cyst, kerato odontogenic tumor, odontogenic keratocyst, and jaws cystic lesion. The eligibility criteria for selecting articles were: to be in the English language, stu
... Show MoreDisease diagnosis with computer-aided methods has been extensively studied and applied in diagnosing and monitoring of several chronic diseases. Early detection and risk assessment of breast diseases based on clinical data is helpful for doctors to make early diagnosis and monitor the disease progression. The purpose of this study is to exploit the Convolutional Neural Network (CNN) in discriminating breast MRI scans into pathological and healthy. In this study, a fully automated and efficient deep features extraction algorithm that exploits the spatial information obtained from both T2W-TSE and STIR MRI sequences to discriminate between pathological and healthy breast MRI scans. The breast MRI scans are preprocessed prior to the feature
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