Background:

Multiple sclerosis is a chronic disease believed to be the result of autoimmune disorders of the central nervous system, characterised by inflammation, demyelination, and axonal transection, affecting primarily young adults. Disease modifying therapies have become widely used, and the rapid development of these drugs highlighted the need to update our knowledge on their short- and long-term safety profile.

Objective:

The study aim is to evaluate the impact of disease-modifying treatments on thyroid functions and thyroid autoantibodies with subsequent effects on the outcome of the disease.

Materials and Methods:

A retro prospective study

The paper presents the design of a system consisting of a solar panel with Single Input/Multiple Outputs (DC-DC) Buck Converter by using Simulink dialogue box tools in MATLAB software package for simulation the system. Maximum Power Point Tracking (MPPT) technique depending on Perturb and Observe (P&O) algorithm is used to control the output power of the converter and increase the efficiency of the system. The characteristics of the MSX-60 PV module is chosen in design of the system, whereas the electrical characteristics (P-V, I-V and P-I curves) for the module are achieved, that is affected by the solar radiation and temperature variations. The proposed design module has been found to be stable for any change in atmospheric tempera

Problem: Cancer is regarded as one of the world's deadliest diseases. Machine learning and its new branch (deep learning) algorithms can facilitate the way of dealing with cancer, especially in the field of cancer prevention and detection. Traditional ways of analyzing cancer data have their limits, and cancer data is growing quickly. This makes it possible for deep learning to move forward with its powerful abilities to analyze and process cancer data. Aims: In the current study, a deep-learning medical support system for the prediction of lung cancer is presented. Methods: The study uses three different deep learning models (EfficientNetB3, ResNet50 and ResNet101) with the transfer learning concept. The three models are trained using a

In this research , we study the inverse Gompertz distribution (IG) and estimate the  survival function of the distribution , and the survival function was evaluated using three methods (the Maximum likelihood, least squares, and percentiles estimators) and choosing the best method estimation ,as it was found that the best method for estimating the survival function is the squares-least method because it has the lowest IMSE and for all sample sizes

In this research , we study the inverse Gompertz distribution (IG) and estimate the  survival function of the distribution , and the survival function was evaluated using three methods (the Maximum likelihood, least squares, and percentiles estimators) and choosing the best method estimation ,as it was found that the best method for estimating the survival function is the squares-least method because it has the lowest IMSE and for all sample sizes

Background:  Knee osteoarthritis (KOA) is a common joint disorder leading to considerable pain and locomotor disability in lower limb function. Locomotor disability, which is difficulty in activities of daily living related to lower limb function, can be the consequence of KOA, so early diagnosis and management may improve quality of life.

Objective: To assess the contribution of radiological osteoarthritis of the knees to disability in the activities of daily living related to lower limb function.

 Methods: One hundred twenty Iraqi KOA patients (104 females and 16 males) who were attending to Rheumatology Unit, Full history was taken and complete clinical exami

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