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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
Wed Nov 01 2023
Journal Name
Clinical Epidemiology And Global Health
The association of interleukin-10 single nucleotide polymorphisms (rs1800871) and serum levels in Iraqi patients with celiac disease: A case-control study
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Publication Date
Sun Feb 10 2019
Journal Name
Journal Of The College Of Education For Women
IMPLEMENTATION OF THE SKIP LIST DATA STRUCTURE WITH IT'S UPDATE OPERATIONS
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A skip list data structure is really just a simulation of a binary search tree. Skip lists algorithm are simpler, faster and use less space. this data structure conceptually uses parallel sorted linked lists. Searching in a skip list is more difficult than searching in a regular sorted linked list. Because a skip list is a two dimensional data structure, it is implemented using a two dimensional network of nodes with four pointers. the implementation of the search, insert and delete operation taking a time of upto . The skip list could be modified to implement the order statistic operations of RANKand SEARCH BY RANK while maintaining the same expected time. Keywords:skip list , parallel linked list , randomized algorithm , rank.

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Publication Date
Tue Oct 01 2019
Journal Name
Ieee Xplore
The Internet of Everything Based Smart Systems: Applications and Challenges
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Smart systems are the trend for modern organizations and should meet the quality of services that expect to produce. Internet of Everything (IoE) helped smart systems to adopt microcontrollers for improving the performance. Analyzing and controlling data in such a system are critical issues. In this study, a survey of IoE systems conducted to show how to apply a suitable model that meets such system requirements. The analysis of some microcontroller boards is explored based on known features. Factors for applying IoE devices have been defined such as connectivity, power consumption, compatibility, and cost. Different methods have been explained as an overview of applying IoE systems. Further, different approaches for applying IoE technology

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Publication Date
Mon Sep 09 2024
Journal Name
Al-rafidain Journal Of Medical Sciences ( Issn 2789-3219 )
Association of hsCRP and Serum Kalirin Levels with the Development and Severity of Premature Coronary Artery Disease in Iraqi Patients
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Background: Coronary artery disease (CAD) is a major contributor to morbidity and mortality worldwide. Early-onset CAD, also known as PCAD, is a severe form of CAD associated with high mortality and a poor prognosis. Early diagnosis is crucial to reducing complications. While hsCRP is an established biomarker for CAD, kalirin is a potential novel biomarker due to its role in promoting smooth muscle proliferation and endothelial dysfunction. Objective: To evaluate the relationship between serum kalirin and hsCRP levels with the presence and severity of PCAD and to compare the diagnostic value of both biomarkers. Method: The study recruited 92 participants into two groups: the PCAD group (46) included patients with confirmed CAD by an

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Publication Date
Wed Feb 01 2023
Journal Name
Baghdad Science Journal
Synthesis, Characterization, and Thermal Analysis of a New Acidicazo Ligand's Metal Complexes
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The researchers wanted to make a new azo imidazole as a follow-up to their previous work. The ligand 4-[(2-Amino-4-phenylazo)-methyl]-cyclohexane carboxylic acid as a derivative of trans-4-(aminomethyl) cyclohexane carboxylic acid diazonium salt, and synthesis a series of its chelate complexes with metalions, characterized these compounds using a variety technique, including elemental analysis, FTIR, LC-Mass, 1H-NMRand UV-Vis spectral process as well TGA, conductivity and magnetic quantifications. Analytical data showed that the Co (II) complex out to 1:1 metal-ligand ratio with square planner and tetrahedral geometry, respectively while 1:2 metal-ligand ratio in the Cu(II), Cr(III), Mn(II), Zn(II), Ru(III)and Rh(III)complexes

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Publication Date
Thu Dec 01 2016
Journal Name
Al.qadisiya Journal For The Sciences Of Physical Education
Comparing self-learning associated with the model and learning reverse fashioned way of partial way to learn Olympic lifts for beginners
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Abstract The purpose of this study, teach the art of performing Olympic lifts (snatch and, clean and jerk) using the two methods are instructional (self-learning associated with the model) and (reverse style of partial way). Identify the effectiveness of these methods in learning the art of performance and style of the best Olympic lifting in the learning and retention of novice for Olympic lifts. The research sample consisted of 16 lifters were selected purposively representing specialist center for the care of athletic talent to weightlifting for ages 14 years. The sample was divided into two experimental, Each group (8) eight weightlifters. The experimental group used the style of the first self-learning associated with the m

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Publication Date
Thu Feb 01 2024
Journal Name
Baghdad Science Journal
Traditional and molecular methods for diagnosing bacterial meningitis in Erbil city, Iraq
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Bacterial meningitis is a leading cause of illness and death worldwide. It is crucial for clinical and public health care, as well as disease control, to identify the meningitis-causing agent promptly. Between June 2021-February 2022, a total of 100 cerebrospinal fluid (CSF) and blood samples were collected from suspected cases of meningitis admitted to Raparin Paediatric Teaching Hospital, Erbil city-Iraq. Cytochemical, cultural, and biochemical tests were conducted, and confirmed by molecular techniques. Bacterial culture findings were positive in 7% of CSF samples and just one positive among blood samples. The most common pathogens found by cultural characteristics and VITEK 2 Compact System were Staphylococcus sciuri in two

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Publication Date
Wed Aug 05 2026
Journal Name
Al–bahith Al–a'alami
The Challenges of Forming A Culture of Change in Iraq (Self-Obstacles to the Media Role)
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The Iraqi culture faced a set of challenges that can be diagnosed with the most prominent features as follows:

  1. The dominance of authoritarian political systems which entails authoritarian regimes with the absence of contemporary political concepts of human rights.
  2. The prevalence of non- informed cultural systems which have the shortage of capabilities that enable them to activate cultural elements in positive references, historical, or seclusion on itself and not be able to interact with the current active cultures.
  3. Stagnant economic conditions have not had a decent life for individuals, or a certain level of well-being, as well as poor services and others.
  4. Social life controlled by the prevai

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Publication Date
Fri Aug 22 2025
Journal Name
Frontiers In Political Science
The role of identity in a multilevel interdependence in international relations: exploring popular understandings of international politics
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This study investigates the role of identity as a critical factor in mediating the relationship between local and regional politics within the broader context of international relations (IR). While identity is frequently acknowledged as a catalyst for political instability and conflict, its function in fostering interdependence across political levels remains underexplored, particularly through empirical research. To address this gap, the study adopts a quantitative methodology, drawing on theories of identity politics and interdependence. A structured survey was administered to assess public perceptions of identity's influence on international engagement and its bridging role between domestic and regional political dynamics. The fi

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Publication Date
Fri Mar 31 2017
Journal Name
Al-khwarizmi Engineering Journal
Big-data Management using Map Reduce on Cloud: Case study, EEG Images' Data
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Database is characterized as an arrangement of data that is sorted out and disseminated in a way that allows the client to get to the data being put away in a simple and more helpful way. However, in the era of big-data the traditional methods of data analytics may not be able to manage and process the large amount of data. In order to develop an efficient way of handling big-data, this work studies the use of Map-Reduce technique to handle big-data distributed on the cloud. This approach was evaluated using Hadoop server and applied on EEG Big-data as a case study. The proposed approach showed clear enhancement for managing and processing the EEG Big-data with average of 50% reduction on response time. The obtained results provide EEG r

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