Temporomandibular disorders (TMDs) were investigated in 143 pretreatment orthodontic patients (43 males and 102 females) whose age ranged between 10-25 years at the College of Dentistry, University of Baghdad, Iraq. The study was undertaken to elucidate the prevalence and severity of TMDs in malocclusion patients and to defme the relationships between malocclusion and TMDs. The clinical signs and subjective symptoms were recorded according to the principles introduced by Helkimo (1974b). Subjective symptoms were reported by 65.7% of the patients with 22.40/0 described as severe, and the most common symptoms were TMJ sounds and feeling offatigue. Clinical signs were observed in 81.8% of the sample with 22.4 and 6.3% described as moderate and

Machine Learning (ML) algorithms are increasingly being utilized in the medical field to manage and diagnose diseases, leading to improved patient treatment and disease management. Several recent studies have found that Covid-19 patients have a higher incidence of blood clots, and understanding the pathological pathways that lead to blood clot formation (thrombogenesis) is critical. Current methods of reporting thrombogenesis-related fluid dynamic metrics for patient-specific anatomies are based on computational fluid dynamics (CFD) analysis, which can take weeks to months for a single patient. In this paper, we propose a ML-based method for rapid thrombogenesis prediction in the carotid artery of Covid-19 patients. Our proposed system aims

Background: Acromegaly is an uncommon, chronic, debilitating condition characterized by hyperinsulinism, insulin resistance, diabetes and prediabetes. One possibility for managing acromegaly's questionable influence on glucose homeostasis is the somatostatin analogues. Aim: To analyze the frequency and risk factors for impaired glucose homeostasis in acromegaly patients treated with depot long-acting octreotide (octreotide LAR), as well as the relationship between risk and treatment duration. Methods: The study included 52 Iraqi adults with acromegaly receiving octreotide LAR. Demographic, anthropometric, and clinical data were collected, as well as the duration of Octreotide LAR administration. Growth hormone, IGF-1, and adenoma si

Bedside clinical teaching is a fundamental part of the medical education that offers invaluable opportunities for the students to build and improve their clinical and communication skills. However, there is a growing concern about the increasing refusal of patients to participate in clinical sessions, especially in certain settings where there are sensitive cultural traditions and decreased trust in institutions.

Shear wave velocity is an important feature in the seismic exploration that could be utilized in reservoir development strategy and characterization. Its vital applications in petrophysics, seismic, and geomechanics to predict rock elastic and inelastic properties are essential elements of good stability and fracturing orientation, identification of matrix mineral and gas-bearing formations. However, the shear wave velocity that is usually obtained from core analysis which is an expensive and time-consuming process and dipole sonic imager tool is not commonly available in all wells. In this study, a statistical method is presented to predict shear wave velocity from wireline log data. The model concentrated to predict shear wave velocity fr

This study relates to  the estimation of  a simultaneous equations system for the Tobit model where the dependent variables  ( )  are limited, and this will affect the method to choose the good estimator. So, we will use new estimations methods  different from the classical methods, which if used in such a case, will produce biased and inconsistent estimators which is (Nelson-Olson) method  and  Two- Stage limited dependent variables(2SLDV) method  to get of estimators that hold characteristics the good estimator .

That is , parameters will be estim