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
In recent years, Wireless Sensor Networks (WSNs) are attracting more attention in many fields as they are extensively used in a wide range of applications, such as environment monitoring, the Internet of Things, industrial operation control, electric distribution, and the oil industry. One of the major concerns in these networks is the limited energy sources. Clustering and routing algorithms represent one of the critical issues that directly contribute to power consumption in WSNs. Therefore, optimization techniques and routing protocols for such networks have to be studied and developed. This paper focuses on the most recent studies and algorithms that handle energy-efficiency clustering and routing in WSNs. In addition, the prime
... Show MoreIncreasing requests for modified and personalized pharmaceutics and medical materials makes the implementation of additive manufacturing increased rapidly in recent years. 3D printing has been involved numerous advantages in case of reduction in waste, flexibility in the design, and minimizing the high cost of intended products for bulk production of. Several of 3D printing technologies have been developed to fabricate novel solid dosage forms, including selective laser sintering, binder deposition, stereolithography, inkjet printing, extrusion-based printing, and fused deposition modeling. The selection of 3D printing techniques depends on their compatibility with the printed drug products. This review intent to provide a perspecti
... Show MoreWater saturation is the most significant characteristic for reservoir characterization in order to assess oil reserves; this paper reviewed the concepts and applications of both classic and new approaches to determine water saturation. so, this work guides the reader to realize and distinguish between various strategies to obtain an appropriate water saturation value from electrical logging in both resistivity and dielectric has been studied, and the most well-known models in clean and shaly formation have been demonstrated. The Nuclear Magnetic Resonance in conventional and nonconventional reservoirs has been reviewed and understood as the major feature of this approach to estimate Water Saturation based on T2 distribution. Artific
... Show MoreSlow learning becomes a problem in the present , where it comprises ratio musnt ignore in every school . So , its one of education problems facing by parents and teachers .
Slow learning subject regard of new subject attract the attention in the last years of the 20th century where the attention was focusing on the other disabilities but the existence of number of healthy children suffering from Learning problems attract the attention of the researchers .
So , this study aims at recognizing the degree of self , concept among slow learner students and the differences significance of self concept according to sex and academic degree of parents variables.
Because there is not tool , the researcher build a
... Show MoreObjective (s): To assess the QoL of children age from (8- lessthan13) years with acute lymphocytic leukemia undergoing chemotherapy and to find out the relationship between the QoL of children with acute lymphocytic leukemia and their illness history.
Methodology: A descriptive study included (40) children with acute lymphocytic leukemia who were ranged between (8 - less than 13 years) at the Hematology Center in Medical City for the period from 4th March 2021 to 1st September 2021. The sample was non-probability (purposive) sample of children (male and female). A questionnaire designed with 2 main parts was used. The first part focused on sociodemographic characterist
... Show MoreIraq has confronted a huge political transformations after 2003 which resembled and presented rapid changes from totalitarian regime into democracy's system , this phenomenon has become a feature embodied in a new political system, specifically is being a price for previous deprivation and despotism .So that, the nature of political work has been changed as a result of practicing new democratic values ,but the real challenges appeared by depending on the conformity and political compromise in dealing with all of crises and problems in the political life .
The future of political work in this nascent democracy could be prepared according to fulfillment an active doings values stretched on national unity and forgiveness from one side ,t
This narrative review focused on research investigating the impact of loneliness on the prevalence of dementia and its relationship with other risk factors. A comprehensive and rigorous search was conducted using a variety of scientific databases with specific keywords to identify all prior studies that examined the correlation between dementia and loneliness. The inquiry was confined to articles published in English from January 2017 to March 2024. The narrative review identified a consensus regarding the role of loneliness in enhancing the risk of all‐cause dementia, with a particular emphasis on the subjective perception of loneliness. This phenomenon may be caused by the sensations of exclusion, discrimination, and alienation that are
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