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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
Mon Jan 01 2024
Journal Name
Bio Web Of Conferences
Concepts of statistical learning and classification in machine learning: An overview
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Statistical learning theory serves as the foundational bedrock of Machine learning (ML), which in turn represents the backbone of artificial intelligence, ushering in innovative solutions for real-world challenges. Its origins can be linked to the point where statistics and the field of computing meet, evolving into a distinct scientific discipline. Machine learning can be distinguished by its fundamental branches, encompassing supervised learning, unsupervised learning, semi-supervised learning, and reinforcement learning. Within this tapestry, supervised learning takes center stage, divided in two fundamental forms: classification and regression. Regression is tailored for continuous outcomes, while classification specializes in c

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Publication Date
Fri Mar 03 2023
Journal Name
The Egyptian Journal Of Hospital Medicine
Immunological Assessment of Human Adenosine Deaminase Activity in Iraqi Female With Thyroid Autoimmune Disease
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Human Adenosine deaminase is an essential enzyme for modulating the bioactivity of thyroid hormones, and It is important for the maturation and differentiation of lymphocytes, although its clinical importance in thyroid diseases have yet to be identified. Objective: The aim of the current study is to determine the Adenosine deaminase concentration in healthy controls, and in autoimmune thyroid diseases such as Graves' Disease, and Hashimoto's Thyroiditis. Patients and methods: A total of 183 serum specimens of 103 female patients with autoimmune thyroid diseases and 80 healthy control groups were included in this study and collected from the Baghdad Medical City, Iraq. Quantitative Human Adenosine Deaminase ELISA kits were used to estimate

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Publication Date
Thu Sep 01 2022
Journal Name
Iraqi Journal Of Computers, Communications, Control And Systems Engineering
A Framework for Predicting Airfare Prices Using Machine Learning
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Many academics have concentrated on applying machine learning to retrieve information from databases to enable researchers to perform better. A difficult issue in prediction models is the selection of practical strategies that yield satisfactory forecast accuracy. Traditional software testing techniques have been extended to testing machine learning systems; however, they are insufficient for the latter because of the diversity of problems that machine learning systems create. Hence, the proposed methodologies were used to predict flight prices. A variety of artificial intelligence algorithms are used to attain the required, such as Bayesian modeling techniques such as Stochastic Gradient Descent (SGD), Adaptive boosting (ADA), Decision Tre

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Publication Date
Fri Sep 30 2022
Journal Name
Iraqi Journal Of Computer, Communication, Control And System Engineering
A Framework for Predicting Airfare Prices Using Machine Learning
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Many academics have concentrated on applying machine learning to retrieve information from databases to enable researchers to perform better. A difficult issue in prediction models is the selection of practical strategies that yield satisfactory forecast accuracy. Traditional software testing techniques have been extended to testing machine learning systems; however, they are insufficient for the latter because of the diversity of problems that machine learning systems create. Hence, the proposed methodologies were used to predict flight prices. A variety of artificial intelligence algorithms are used to attain the required, such as Bayesian modeling techniques such as Stochastic Gradient Descent (SGD), Adaptive boosting (ADA), Deci

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Publication Date
Mon Jan 01 2024
Journal Name
Ieee Access
Patient Monitoring System Based on Internet of Things: A Review and Related Challenges With Open Research Issues
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Publication Date
Sun Feb 01 2015
Journal Name
Journal Of Economics And Administrative Sciences
Diagnosing the information technology (IT) capabilities and It’s Effect to Achieving A competitive Superiority Analytical Research in Baghdad soft drinks Company/Al- Zafaraniya
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Purpose: The current research attempts to diagnosis the reflection level of Information Technology (IT) Capabilities (Architectural, infrastructure, human resources, relationships resources, and dynamic capabilities) at Baghdad soft drinks Company/Al- Zafaraniya to achieving the competitive superiority represented by indicators (Cost, quality, flexibility, delivery and innovation). Recognizing the importance of the subjects studied, and because of the importance of the expected results of the field under consideration.

Design/Methodology/Approach: The experimental method has been used, the questionnaire used to collect th

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Publication Date
Fri Nov 11 2022
Journal Name
Surgical Neurology International
Brown-Sequard syndrome associated with a spinal cord injury caused by a retained screwdriver: A case report and literature review
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Background:

Nonmissile penetrating spine injury (NMPSI) represents a small percent of spinal cord injuries (SCIs), estimated at 0.8% in Western countries. Regarding the causes, an NMPSI injury caused by a screwdriver is rare. This study reports a case of a retained double-headed screwdriver in a 37-year-old man who sustained a stab injury to the back of the neck, leaving the patient with a C4 Brown-Sequard syndrome (BSS). We discuss the intricacies of the surgical management of such cases with a literature review.

Methods:

PubMed database was searched by the following combined formula of medical subjects headings,

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Publication Date
Wed Sep 15 2021
Journal Name
Al-academy
The impact of e-learning on the cognitive level in the Corona crisis: أسماء غازي عبد
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E-learning is a necessity imposed by the Corona pandemic, which has disrupted various educational institutions in the world, but some of these institutions have not been affected and education has continued with them, due to their flexible educational system that was able to employ technology in the continuity of the educational process in the so-called e-learning, because It has characteristics that make it the most suitable alternative to avoid the consequences of the Corona pandemic and its damage to the educational process, as e-learning is one of the modern methods that contribute to enhancing the effectiveness of the learner, and enabling him to assume greater responsibility compared to traditional education, so the learner becomes

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Publication Date
Sat Jul 01 2023
Journal Name
Analytical Science & Technology
Metal complexes of alizarin and their biological and industrial applications: A literature review
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Alizarin is one of the popularly used and wide separated compounds with a chemical name (1,2- dihydroxy-9,10-anthraquinone) which belong to the anthraquinones family that contain three aromatic conjugated rings and in the central rings it contains two ketonic groups.1

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Publication Date
Sun Mar 19 2023
Journal Name
Journal Of Educational And Psychological Researches
Cognitive Absorption and E-learning Readiness in Learning Digitization among Preparatory Stage in Qatar
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Abstract

The study aims to examine the relationships between cognitive absorption and E-Learning readiness in the preparatory stage. The study sample consisted of (190) students who were chosen randomly. The Researcher has developed the cognitive absorption and E-Learning readiness scales. A correlational descriptive approach was adopted. The research revealed that there is a positive statistical relationship between cognitive absorption and eLearning readiness.

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