Thyroid disease is a common disease affecting millions worldwide. Early diagnosis and treatment of thyroid disease can help prevent more serious complications and improve long-term health outcomes. However, thyroid disease diagnosis can be challenging due to its variable symptoms and limited diagnostic tests. By processing enormous amounts of data and seeing trends that may not be immediately evident to human doctors, Machine Learning (ML) algorithms may be capable of increasing the accuracy with which thyroid disease is diagnosed. This study seeks to discover the most recent ML-based and data-driven developments and strategies for diagnosing thyroid disease while considering the challenges associated with imbalanced data in thyroid disease predictions. A systematic literature review (SLR) strategy is used in this study to give a comprehensive overview of the existing literature on forecasting data on thyroid disease diagnosed using ML. This study includes 168 articles published between 2013 and 2022, gathered from high-quality journals and applied meta-analysis. The thyroid disease diagnoses (TDD) category, techniques, applications, and solutions were among the many elements considered and researched when reviewing the 41 articles of cited literature used in this research. According to our SLR, the current technique's actual application and efficacy are constrained by several outstanding issues associated with imbalance. In TDD, the technique of ML increases data-driven decision-making. In the Meta-analysis, 168 documents have been processed, and 41 documents on TDD are included for observation analysis. The limits of ML that are discussed in the discussion sections may guide the direction of future research. Regardless, this study predicts that ML-based thyroid disease detection with imbalanced data and other novel approaches may reveal numerous unrealised possibilities in the future
Background: Tumor necrosis factor-alpha (TNF-α) and interleukins play important roles in the pathogenesis of rheumatoid arthritis (RA). Genetic research has been employed to find many of the missing connections between genetic risk variations and causal genetic components. Objective: The goal of this study is to look at the genetic variations of TNF-α and interleukins in Iraqi RA patients and see how they relate to disease severity or response to biological therapy. Method: Using specific keywords, the authors conducted a systematic and comprehensive search to identify relevant Iraqi studies examining the genetic variations of TNF-α and interleukins in Iraqi RA patients and how they relate to disease severity or response to biolo
... Show MoreBackground: Multiple sclerosis (MS) is an inflammatory disease of the central nervous system, in which the myelin sheaths got injured. The prevalence of MS is on grow, as well as, it affects the young ages. Females are most common to have MS compared to males. Oxidative stress is the situation of imbalance between oxidants (free radicals and reactive oxygen species (ROS)) and antioxidants in a living system, in which either the oxidants are elevated or antioxidants are reduced, or sometimes both. ROS and oxidative stress have been implicated in the progression of many degenerative diseases, which is important in cracking the unrevealed mysteries of MS. In this review article, some of the proposed mechanisms that link oxidative stres
... Show MorePurpose: Determining and identifying the relationships of smart strategic education systems and their potential effects on sustainable success in managing clouding electronic business networks according to green, economic and environmental logic based on vigilance and awareness of the strategic mind.
Design: Designing a hypothetical model that reveals the role and investigating audit and cloud electronic governance according to a philosophy that highlights smart strategic learning processes, identifying its assumptions in cloud spaces, choosing its tools, what it costs to devise expert minds, and strategic intelligence.
Methodology:
Classification of imbalanced data is an important issue. Many algorithms have been developed for classification, such as Back Propagation (BP) neural networks, decision tree, Bayesian networks etc., and have been used repeatedly in many fields. These algorithms speak of the problem of imbalanced data, where there are situations that belong to more classes than others. Imbalanced data result in poor performance and bias to a class without other classes. In this paper, we proposed three techniques based on the Over-Sampling (O.S.) technique for processing imbalanced dataset and redistributing it and converting it into balanced dataset. These techniques are (Improved Synthetic Minority Over-Sampling Technique (Improved SMOTE), Border
... Show MoreThe research includes a clinical study of Preptin with other parameters. The normal value of preptin in hypothyroidism (2638.4±280.0) in female while (2960.4±256.6) in male, in hyperthyroidism (589.0±90.1) in male, while in female (993.2±103.9), diabetes (2465.6±282.4) in female, in male (2085.5±282.8), in diabetes & hypothyroidism (3314.3±177.3) in male,(3179.4±265.7) in female, but control group in female (427.8±60.4), in male (384.7±62.4) at age (20-45) years they were divided into five groups: group one (G1) consisted of 30 hypothyroidism. The two group (G2) consisted of 30 patients with hyperthyroidism. And three group (G3) consisted of 30 healthy group, four group (G4) consisted of 30 patient with diabetes, and five group (G
... Show MoreThe study aims to measure the level of academic stress in the e-learning environment in three areas, students and their dealing with classmates, dealing with the professor and technical skills, and the nature and content of the curriculum among graduate students in the College of Education at King Khalid University during COVID-19 pandemic. This study was descriptive in nature (survey, comparative). The sample consisted of (512) male and female graduate students in the master's and doctoral programs. The Academic Stress Scale in the E-learning Environment designed by Amer (2021) was used. The results indicated a high level of academic stress among graduate students in the e-learning environment. The study also found that there were stati
... Show MoreThe importance of this study lies in shedding the light on the impact of Islam and Prophet Mohammed (peace be upon him) on the western culture and English literature in particular. While some writers were looking at Islam as a dangerous element, others were completely taken by the oriental spirit of Arabic and Islamic culture and glorifying it. Writers from Chaucer to later ones mostly make references to this impact showing how vast was the gap of misunderstanding between the east and the West. Thus, this study aims at breaking the barrier between East and West in its three sections as it introduces the meaning of Islam and its common features with other religions in the first section. The second section briefly presents writers’ reflecti
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