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: Chronic obstructive pulmonary disease (COPD) is a progressive airflow limitation that is preventable but not curable. It is associated with persistent symptoms that cause a considerable burden on individual productivity at work, and daily activities, and reduced quality of life, also burdening the healthcare system and society. Objectives: The study aims to measure the burden of COPD on patients in terms of daily activities and work productivity. It also seeks to investigate some inflammatory biomarkers' levels and their correlation with selected outcomes. Patients and Methods: A cross-sectional study on 120 stable COPD patients who were diagnosed and treated according to the GOLD guidelines at Kirkuk General Hospital's
... Show MoreRealizing the full potential of wireless sensor networks (WSNs) highlights many design issues, particularly the trade-offs concerning multiple conflicting improvements such as maximizing the route overlapping for efficient data aggregation and minimizing the total link cost. While the issues of data aggregation routing protocols and link cost function in a WSNs have been comprehensively considered in the literature, a trade-off improvement between these two has not yet been addressed. In this paper, a comprehensive weight for trade-off between different objectives has been employed, the so-called weighted data aggregation routing strategy (WDARS) which aims to maximize the overlap routes for efficient data aggregation and link cost
... Show MoreThe aim of the research is to provide an analytical study to promote financial inclusion in Iraq by clarifying the opportunities and challenges of the economic and demographic situation in Iraq, studying the structure of the financial system and introducing non-bank financial institutions operating in Iraq, and using the descriptive approach. Analytical in the study of the phenomenon of research, the research reached a number of conclusions, the most prominent of which were:
- Iraqi society is a young society.
- The majority of the population is 70 percent. They live almost in urban areas.
- The coverage of bank branch networks is concentrated in only four provinces, leaving other provinces outside financial
Within the framework of big data, energy issues are highly significant. Despite the significance of energy, theoretical studies focusing primarily on the issue of energy within big data analytics in relation to computational intelligent algorithms are scarce. The purpose of this study is to explore the theoretical aspects of energy issues in big data analytics in relation to computational intelligent algorithms since this is critical in exploring the emperica aspects of big data. In this chapter, we present a theoretical study of energy issues related to applications of computational intelligent algorithms in big data analytics. This work highlights that big data analytics using computational intelligent algorithms generates a very high amo
... Show MoreEstimating the semantic similarity between short texts plays an increasingly prominent role in many fields related to text mining and natural language processing applications, especially with the large increase in the volume of textual data that is produced daily. Traditional approaches for calculating the degree of similarity between two texts, based on the words they share, do not perform well with short texts because two similar texts may be written in different terms by employing synonyms. As a result, short texts should be semantically compared. In this paper, a semantic similarity measurement method between texts is presented which combines knowledge-based and corpus-based semantic information to build a semantic network that repre
... Show Moreاستهدف البحث تشخيص وتحليل الاسباب التي تجعل المرأة العراقية أكثر تأثراً من الرجل بعوامل التغيرات المناخية، فضلاً عن زيادة الوعي بقضية المرأة في هذا المجال، لأن موضوع دمجها في صياغة السياسات والاستراتيجيات المتعلقة بالتغير المناخي أصبح قضية عالمية، ويحتل مرتبة متقدمة في مؤشرات تحقيق أهداف التنمية المستدامة، وأستخدمت الباحثة المنهج الوصفي والتحليلي والاحصائي في تحليل محاور البحث، وتوصل البحث الى إستن
... Show Morethe traumatic memory of their ancestors. The novel navigates sites of trauma, memory, and blues music while resisting the bourgeoisie-capitalist relationships that permeated not only white society but also African American communities. Jones’s novel presents the plight of an African American woman, Ursa, caught between the memory of her enslaved foremothers and her life in an emancipated world. The physical and spiritual exploitation of African American women who bear witness to the history of slavery in Corregidora materializes black women’s individuality. This article is framed by trauma studies as well as the Marxists’ concepts of commodification, accumulation, and production. Ursa, one of the Corregidora women, represents
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