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Exploring the Challenges of Diagnosing Thyroid Disease with Imbalanced Data and Machine Learning: A Systematic Literature Review
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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

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Publication Date
Fri Dec 02 2022
Journal Name
Periodicals Of Engineering And Natural Sciences
Histological and immunohistochemical study of thyroid gland in Caucasian squirrel (Sciurus anamalus) (Gmelin, 1778) by using marker (Anti-Thyroglobulin, Code IR5090)
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The current study is designed to investigate the histological and immunohistochemical characteristics of the thyroid gland in adult male Sciurus anamalus. This study found that the thyroid gland of the Caucasian squirrel is located in the neck area, below the larynx, on both sides of the trachea. It has two lobes (right and left) with cylindrical shape. The histological studies revealed that the thyroid gland is surrounded by a capsule which consists of connective tissue and forming of two layers which are outer layer and inner layer, and a layer of adipose tissue appears overlapping the outer layer. The inner tissue of the gland consists of follicles with different shapes and sizes, and is lined with simple cuboidal epithelial tissue (foll

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Publication Date
Thu Jan 01 2026
Journal Name
Sustainable Civil Infrastructures
The Impact of the Jesko Strategy on Learning the Skill of Smashing in Volleyball
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Publication Date
Wed Dec 23 2020
Journal Name
Iraqi Journal For Electrical And Electronic Engineering
Heuristic and Meta-Heuristic Optimization Models for Task Scheduling in Cloud-Fog Systems: A Review
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Nowadays, cloud computing has attracted the attention of large companies due to its high potential, flexibility, and profitability in providing multi-sources of hardware and software to serve the connected users. Given the scale of modern data centers and the dynamic nature of their resource provisioning, we need effective scheduling techniques to manage these resources while satisfying both the cloud providers and cloud users goals. Task scheduling in cloud computing is considered as NP-hard problem which cannot be easily solved by classical optimization methods. Thus, both heuristic and meta-heuristic techniques have been utilized to provide optimal or near-optimal solutions within an acceptable time frame for such problems. In th

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Publication Date
Thu Jan 30 2020
Journal Name
Telecommunication Systems
Nature-inspired optimization algorithms for community detection in complex networks: a review and future trends
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Publication Date
Sun Jun 30 2024
Journal Name
Wasit Journal For Pure Sciences
Design Polynomial IIR Digital Filters of the Integer Parameters Space Use to Compress Image Data
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Polynomial IIR digital filters play a crucial role in the process of image data compression. The main purpose of designing polynomial IIR digital filters of the integer parameters space and introduce efficient filters to compress image data using a singular value decomposition algorithm. The proposed work is designed to break down the complex topic into bite-sized pieces of image data compression through the lens of compression image data using Infinite Impulse Response Filters. The frequency response of the filters is measured using a real signal with an automated panoramic measuring system developed in the virtual instrument environment. The analysis of the output signal showed that there are no limit cycles with a maximum radius

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Publication Date
Thu Oct 01 2015
Journal Name
Al-academy
The Factors influencing to the cognition operation & its Data: وفاء جاسم محمد
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The present research deals with the influencing factors which depends on the way perceptual of the graphic designer which enters in the design logos of the loco European health, where the search include four chapters, the researcher reviewed in the chapter 0ne the methodical frame of the research ,as reviewed in the second chapter the theoretical frame, and the previous studies which included three sections, the first section included the perceptual understandable and types of it, and the second section included the influencing factors in the designer perceptual ways and its division . While the third section included the perceptual in graphic designer through the percepted shapes and the relation with ground and colors for express the i

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Publication Date
Wed Dec 20 2023
Journal Name
Health Education And Health Promotion
Influence of Educational Program of Cholera Disease on Nannies' Practices in the Nurseries
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Publication Date
Mon Jan 19 2026
Journal Name
American Journal Of Alzheimer's Disease & Other Dementias®
Comparison Study of Different Feature Selection Techniques for the Diagnosis of Alzheimer’s Disease
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Objective : Alzheimer’s disease (AD) continues to be a major challenge because handling high-dimensional data is time-consuming and expensive due to its complexity. A large feature space often increases computational costs and reduces model interpretability. This study addresses this problem by evaluating and comparing multiple feature selection techniques to identify the most informative biomarkers for AD diagnosis.

Methods : Our study used data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) to implement and test three feature selection a

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Publication Date
Thu Oct 12 2023
Journal Name
Egyptian Journal Of Biological Pest Control
Evaluation of the effectiveness of some mycorrhizal fungi isolates against charcoal rot disease
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Abstract<sec> <title>Background

The sunflower plants are attacked by serious seed and soil-borne pathogens including charcoal rot disease that caused by Macrophomina phaseolina. This disease has serious damages to sunflower crop. This study aimed to assess the efficacy of Arbuscular mycorrhizal fungus against charcoal rot disease as fungicide alternative.

Results

Morphological and molecular identification was done, using universal primers for molecular identification. Finally, a greenhouse experiment was conducted, and

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Publication Date
Wed Jan 01 2020
Journal Name
Technologies And Materials For Renewable Energy, Environment And Sustainability: Tmrees20
Change detection of the land cover for three decades using remote sensing data and geographic information system
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