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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
Sat Jun 06 2020
Journal Name
Journal Of The College Of Education For Women
Image classification with Deep Convolutional Neural Network Using Tensorflow and Transfer of Learning
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The deep learning algorithm has recently achieved a lot of success, especially in the field of computer vision. This research aims to describe the classification method applied to the dataset of multiple types of images (Synthetic Aperture Radar (SAR) images and non-SAR images). In such a classification, transfer learning was used followed by fine-tuning methods. Besides, pre-trained architectures were used on the known image database ImageNet. The model VGG16 was indeed used as a feature extractor and a new classifier was trained based on extracted features.The input data mainly focused on the dataset consist of five classes including the SAR images class (houses) and the non-SAR images classes (Cats, Dogs, Horses, and Humans). The Conv

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Publication Date
Wed Apr 16 2025
Journal Name
International Journal Of Engineering Pedagogy (ijep)
Utilizing Machine Learning Techniques to Predict University Students' Digital Competence
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Given the importance of possessing the digital competence (DC) required by the technological age, whether for teachers or students and even communities and governments, educational institutions in most countries have sought to benefit from modern technologies brought about by the technological revolution in developing learning and teaching and using modern technologies in providing educational services to learners. Since university students will have the doors to work opened in all fields, the research aims to know their level of DC in artificial intelligence (AI) applications and systems utilizing machine learning (ML) techniques. The descriptive approach was used, as the research community consisted of students from the University

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Publication Date
Wed Aug 31 2022
Journal Name
Al-kindy College Medical Journal
Acute Appendicitis and Multisystemic Inflammatory Syndrome due to COVID-19: a Case Report and Literature Review
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The prevalence of gastrointestinal symptoms of COVID-19 is variable with different types of presentations. Some of them many present with manifestations mimicking surgical emergencies. Yet, the pathophysiology of acute abdomen in the context of COVID-19 remains unclear. We present a case of a previously healthy child who presented with acute appendicitis with multisystemic inflammatory syndrome. We also highlight the necessity of considering the gastrointestinal symptoms of COVID-19 infection in pediatric patients in order to avoid misdiagnosis and further complications.

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Publication Date
Sun Jan 01 2023
Journal Name
مجلة ميسان للدراسات الأكاديمية
Natural Fibers Reinforcement Of Denture Base Materials: Natural Wool Reinforcement:, A Review Of Literature
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Publication Date
Thu Jul 11 2024
Journal Name
Maaen Journal For Medical Sciences
Pharmacological Supplements Efficacy in Management of chronic pain associated with Sickle Cell Disease: A narrative review
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Sickle cell disease (SCD) is a hereditary ailment that can cause severe pain and suffering to people who are affected. However, with continued investment in research and treatment options, we can make progress towards improving the lives of those with SCD. Over 40% of patients experience painful vaso-occlusive crises (VOCs), so we must work towards finding solutions and providing support for those living with this condition, These episodes, a hallmark of SCD, significantly contribute to morbidity, mortality, and a diminished quality of life, while also incurring substantial healthcare costs. Chronic pain particularly affects older adolescents and adults with SCD, with over half reporting daily discomfort. Opioid-based analgesics, though sti

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Publication Date
Sat Jun 01 2013
Journal Name
Journal Of The College Of Basic Education
Beta-2-Microglobulin as a Biomarker in Iraqi Female Patients with Autoimmune Thyroid and Renal Autoimmune Thyroid Diseases
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The present study was performed on 80 female subjects between (30-60) years, who attended the Specialized Center for Endocrinology and Diabetes during the period from April to July; 2011. The subjects were divided into 3 groups : controls , non diabetic autoimmune thyroid patients , and non diabetic autoimmune thyroid patient with renal diseases as complication The results showed a significant increase in serum T 3 T4 levels in hyperthyroidism patients, and significant decrease in serum T3,T4 levels in hypothyroidism patients ,while a significant difference in serum TSH levels in hyperthyroidism and hypothyroidism patients when compared to control group The results show also a significant increase in serum antibodies to thyroid peroxidas

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Publication Date
Fri Feb 01 2019
Journal Name
Journal Of Economics And Administrative Sciences
The impact of organizational learning capabilities on the promotion of knowledge capital Applied research at Wasit University
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Abstract

      The current research aims at identifying any of the dimensions of organizational learning abilities that are more influential in the knowledge capital of the university and the extent to which they can be applied effectively at Wasit University. The current research dealt with organizational learning abilities as an explanatory variable in four dimensions (Experimentation and openness, sharing and transfer of knowledge, dialogue, interaction with the external environment ), and knowledge capital as a transient variable, with four dimensions (human capital, structural capital, client capital, operational capital). The problem of research is the following questio

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Publication Date
Fri Dec 01 2023
Journal Name
Political Sciences Journal
Using the Nudge Theory in Improving Security Policies and Crime Prevention: Integrative Review
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The "Nudge" Theory is considered one of the most recent theories, which is clear in the economic, health, and educational sectors, due to the intensity of studies on it and its applications, but it has not yet been included in crime prevention studies. The use of  Nudge theory appears to enrich the theory in the field of crime prevention, and to provide modern, effective, and implementable mechanisms.

The study deals with the "integrative review" approach, which is a distinctive form of research that generates new knowledge on a topic through reviewing, criticizing, and synthesizing representative literature on the topic in an integrated manner so that new frameworks and perspectives are created around it.

The study is bas

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Publication Date
Tue Jan 02 2018
Journal Name
Journal Of Educational And Psychological Researches
Teaching techniques due to the Brain-based learning theory among math teachers
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The purpose of the study is to identify the teaching techniques that mathematics' teachers use due to the Brain-based learning theory. The sample is composed of (90) teacher: (50) male, (40) female. The results have shown no significant differences between male and female responses' mean. Additionally, through the observation of author, he found a lack of using Brain-based learning techniques. Thus, the researcher recommend that it is necessary to involve teachers in remedial courses to enhance their ability to create a classroom that raise up brain-based learning skills.  

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Publication Date
Tue Aug 29 2023
Journal Name
Geomatics And Environmental Engineering
Challenges and Issues in Spatial Data Infrastructure (SDI) Development in Iraq
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This paper addresses the nature of Spatial Data Infrastructure (SDI), considered as one of the most important concepts to ensure effective functioning in a modern society. It comprises a set of continually developing methods and procedures providing the geospatial base supporting a country’s governmental, environmental, economic, and social activities. In general, the SDI framework consists of the integration of various elements including standards, policies, networks, data, and end users and application areas. The transformation of previously paper-based map data into a digital format, the emergence of GIS, and the Internet and a host of online applications (e.g., environmental impact analysis, navigation, applications of VGI dat

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