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.
Type 2 diabetes mellitus which abbreviate as T2DM is a complex endocrine and metabolic disorder arisingfrom genetic and environmental factors interaction which in turn induce various degrees of insulin functionalalteration on peripheral tissues. Globally, T2DM has develop into a public health problem. Therefore, Thestudy included (75) patients(37 female and 38 males) suffering from T2DM who visit al-kadhimiya teachinghospital with age range 20-80 years and (70) as healthy controls with age range 20-70 years. All studiedgroups were evaluated CMV IgG by ELISA,B. urea, S. Creatinine, cholesterol and triglyceride the resultsshowed that B.urea, S.creatinine and serum cholesterol showed a non-significant differences between studiedgroup,
... Show MoreBackground: Diabetes and periodontitis are considered as chronic diseases with a bidirectional relationship between them. This study aimed to determine and compare the severity of periodontal health status and salivary parameters in diabetic and non-diabetic patients with chronic periodontitis. Materials and Methods: Seventy participants were enrolled in this study. The subjects were divided into three groups: Group I: 25 patients had type 2 diabetes mellitus with chronic periodontitis, Group 2: 25 patients had chronic periodontitis and with no history of any systemic diseases, Group 3: 20 subjects had healthy periodontium and were systemically healthy. Unstimulated whole saliva was collected for measurement of salivary flow rate and pH.
... Show MoreAge, hypertension, and diabetes can cause significant alterations in arterial structure and function, including changes in lumen diameter (LD), intimal-medial thickness (IMT), flow velocities, and arterial compliance. These are also considered risk markers of atherosclerosis and cerebrovascular disease. A difference between right and left carotid artery blood flow and IMT has been reported by some researchers, and a difference in the incidence of nonlacunar stroke has been reported between the right and left brain hemispheres. The aim of this study was to determine whether there are differences between the right and left common carotid arteries and internal carotid arteries in patient
With the fast-growing of neural machine translation (NMT), there is still a lack of insight into the performance of these models on semantically and culturally rich texts, especially between linguistically distant languages like Arabic and English. In this paper, we investigate the performance of two state-of-the-art AI translation systems (ChatGPT, DeepSeek) when translating Arabic texts to English in three different genres: journalistic, literary, and technical. The study utilizes a mixed-method evaluation methodology based on a balanced corpus of 60 Arabic source texts from the three genres. Objective measures, including BLEU and TER, and subjective evaluations from human translators were employed to determine the semantic, contextual an
... Show MoreE-learning is a necessity imposed by the Corona pandemic, which has disrupted various educational institutions in the world, but some of these institutions have not been affected and education has continued with them, due to their flexible educational system that was able to employ technology in the continuity of the educational process in the so-called e-learning, because It has characteristics that make it the most suitable alternative to avoid the consequences of the Corona pandemic and its damage to the educational process, as e-learning is one of the modern methods that contribute to enhancing the effectiveness of the learner, and enabling him to assume greater responsibility compared to traditional education, so the learner becomes
... Show MoreNew trends in teaching and learning theory are considered a theoretical axis
from which came the background that depends on any source, or practice sample or
teaching plane, accuracy and simplicity prevent the development of the teaching
process. Many attempts have come to scene to illuminate the teaching background,
but they have not exceed those remarkable patterns and methods. Thus, the
appearance of the teaching theory have been hindered.
This led to the need for research and development in the field of teaching to
find out a specific teaching theory according to the modern trends and concepts.
Teaching is regarded a humanitarian process which aims at helping those who
want to acquire knowledge, since teach
Detection of early clinical keratoconus (KCN) is a challenging task, even for expert clinicians. In this study, we propose a deep learning (DL) model to address this challenge. We first used Xception and InceptionResNetV2 DL architectures to extract features from three different corneal maps collected from 1371 eyes examined in an eye clinic in Egypt. We then fused features using Xception and InceptionResNetV2 to detect subclinical forms of KCN more accurately and robustly. We obtained an area under the receiver operating characteristic curves (AUC) of 0.99 and an accuracy range of 97–100% to distinguish normal eyes from eyes with subclinical and established KCN. We further validated the model based on an independent dataset with
... Show More