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
This competition between competing forces, organized into axes with conflicting objectives, is reflected in all regional affairs and the goals and interests of countries within them, including Iraq. Among the most important aspects impacted by the repercussions of international and regional competition in the region is Iraqi national security, based on its vital importance in preserving the sovereignty and entity of the Iraqi state, protecting the interests and cohesion of the state and people, ensuring and defending their present and future, and interacting with various regional and international activities. The Kurdistan Region, as an important part of Iraq with its own unique characteristics, may be one of the most important regi
... Show MoreThe current research aims at detecting Brain Dominance Learning Styles distinguished
and ordinary secondary school students (males and females).The researcher adopted Torrance
measure, known as ‘the style of your learning and thinking to measure Brain Dominance
Learning Styles’, the codified version of Joseph Qitami (1986); picture (a). The researcher
verified the standard properties of tool. The final application sample was 352 distinguished
and ordinary students; 176 distinguished male and female students and 176 ordinary male and
female students at the scientific fifth level of secondary school from schools in the province of
Baghdad, AL- KarKh Education Directorates in the First and Second . and who have been
Goal of research is to investigate the impact of the use of effective learning model in the collection of the fourth grade students/Department of physics in the material educational methods and the development of critical thinking .to teach this goal has been formulated hypothesis cefereeten zero subsidiary of the second hypothesis .To investigate the research hypothesis were selected sample of fourth-grade students of the department of physics at the univers
... Show MorePurpose – The Cloud computing (CC) and its services have enabled the information centers of organizations to adapt their informatic and technological infrastructure and making it more appropriate to develop flexible information systems in the light of responding to the informational and knowledge needs of their users. In this context, cloud-data governance has become more complex and dynamic, requiring an in-depth understanding of the data management strategy at these centers in terms of: organizational structure and regulations, people, technology, process, roles and responsibilities. Therefore, our paper discusses these dimensions as challenges that facing information centers in according to their data governance and the impa
... Show MoreBackground: Urolithiasis and hypertension are prevalent and clinically significant conditions in the Middle East, both influenced by shared metabolic and environmental risk factors. Understanding the potential association between them is important for guiding prevention strategies. Objective: To explore the relationship between urolithiasis and hypertension in a sample of Iraqi adult patients. Methods: A cross-sectional observational study was conducted at Alkindy Teaching Hospital, Baghdad, from September 2024 to March 2025. Participants included 237 patients with confirmed urinary tract stones and 244 controls confirmed to be stone-free, matched for age and sex. Exclusion criteria included secondary hypertension, chronic kidney di
... Show MoreIntroduction. The coexistence of non-small cell lung cancer (NSCLC) and chronic obstructive pulmonary disease (COPD) is commonly observed, primarily due to overlapping risk factors like smoking and environmental exposures. This dual diagnosis introduces complex clinical scenarios, often associated with worsened outcomes and heightened vulnerability to treatment-related side effects. Immune checkpoint inhibitors, especially atezolizumab, have emerged as pivotal agents in enhancing clinical outcomes for individuals diagnosed with NSCLC. Recent evidence suggests that atezolizumab remains effective and well-tolerated in NSCLC patients with coexisting COPD. This review evaluates the efficacy and safety of atezolizumab in NSCLC patients with coex
... Show MoreThis research a study model of linear regression problem of autocorrelation of random error is spread when a normal distribution as used in linear regression analysis for relationship between variables and through this relationship can predict the value of a variable with the values of other variables, and was comparing methods (method of least squares, method of the average un-weighted, Thiel method and Laplace method) using the mean square error (MSE) boxes and simulation and the study included fore sizes of samples (15, 30, 60, 100). The results showed that the least-squares method is best, applying the fore methods of buckwheat production data and the cultivated area of the provinces of Iraq for years (2010), (2011), (2012),
... Show MoreWith the vast usage of network services, Security became an important issue for all network types. Various techniques emerged to grant network security; among them is Network Intrusion Detection System (NIDS). Many extant NIDSs actively work against various intrusions, but there are still a number of performance issues including high false alarm rates, and numerous undetected attacks. To keep up with these attacks, some of the academic researchers turned towards machine learning (ML) techniques to create software that automatically predict intrusive and abnormal traffic, another approach is to utilize ML algorithms in enhancing Traditional NIDSs which is a more feasible solution since they are widely spread. To upgrade t
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