Background: Insulin resistance is present in 50% or more of patients with primary hypothyroidism. Metformin can decrease TSH levels in these patients by a complex matter, this can be of great help in clinical practice.

Objective: This study was designed to evaluate the effect of metformin in reducing TSH levels in patients with primary hypothyroidism.

Methods: Hundred patients with primary hypothyroidism, 82 females, 18 males were included in this study, everyone was followed up for two months after adding metformin 850 mg twice daily in addition to thyroxin.

Results: 36 patients (36%) have a normal baseline TSH and no change after 2 months, 64 pa

BACKGROUND: The primary cause of blindness in diabetics is diabetic retinopathy (DR), the most common microvascular complication of diabetes, and visual impairment. Visfatin is an adipocytokine that aids in insulin activity during gestational diabetes and pregnancy.

AIM: This study aimed to estimate serum visfatin levels in DR, proliferative (PDR), non-proliferative (NPDR), and healthy subjects (HS).

MATERIALS AND METHODS: A 120-patient case-control study with a history of T2DM for more than 5 years as well as 30 healthy subjects enrolled in the study. Patients group divided into three sub-groups, DM, PDR, and NPDR. Visfatin levels w

This research deals with unusual approach for analyzing the Simple Linear Regression via Linear Programming by Two - phase method, which is known in Operations Research: “O.R.”. The estimation here is found by solving optimization problem when adding artificial variables: Ri. Another method to analyze the Simple Linear Regression is introduced in this research, where the conditional Median of (y) was taken under consideration by minimizing the Sum of Absolute Residuals instead of finding the conditional Mean of (y) which depends on minimizing the Sum of Squared Residuals, that is called: “Median Regression”. Also, an Iterative Reweighted Least Squared based on the Absolute Residuals as weights is performed here as another method to

Poverty phenomenon is very substantial topic that determines the future of societies and governments and the way that they deals with education, health and economy. Sometimes poverty takes multidimensional trends through education and health. The research aims at studying multidimensional poverty in Iraq by using panelized regression methods, to analyze Big Data sets from demographical surveys collected by the Central Statistical Organization in Iraq. We choose classical penalized regression method represented by The Ridge Regression, Moreover; we choose another penalized method which is the Smooth Integration of Counting and Absolute Deviation (SICA) to analyze Big Data sets related to the different poverty forms in Iraq. Euclidian Distanc

Steganography is the art of secret communication. Its purpose is to hide the presence of information, using, for example, images as covers. The frequency domain is well suited for embedding in image, since hiding in this frequency domain coefficients is robust to many attacks. This paper proposed hiding a secret image of size equal to quarter of the cover one. Set Partitioning in Hierarchal Trees (SPIHT) codec is used to code the secret image to achieve security. The proposed method applies Discrete Multiwavelet Transform (DMWT) for cover image. The coded bit stream of the secret image is embedded in the high frequency subbands of the transformed cover one. A scaling factors ? and ? in frequency domain control the quality of the stego

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