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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
Sun Feb 03 2019
Journal Name
Journal Of The College Of Education For Women
What came as a language in the book to explain Ibn Aqeel on Alfiya Ibn malek
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It is found in the book "Ibn Aqeel: Alfiya Ibn Malek" that there are some linqustical aspected are related to the native tribal speakers like Tamim or Tie or some others. Sometimes in the book he said "some Arabian said without mentioning the name of the tribe.
As weel, he hasn’t mentioned the accent but he does mention the language. In the book, he has brought back the most important and the biqqest Arabian tribes suchas tribes of Hegaz, Tamim, Hatheyal, son of Anber, Tie, Rabia Bin Wael, Bani Katham, Au there, Bani AL Harth, Bani Kalb, Bani Hgim, Zabid, Hamedan, Alia Qais, Bani Ameer and many others. However, the most mentioned tribes were Hegaz and Tami.
Hence, the importance of the book expiain Ibn Aqeel by mentioning these A

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Publication Date
Fri Jan 01 2021
Journal Name
International Journal Of Agricultural And Statistical Sciences
EFFICACY ASSESSMENT OF BLACK PEPPER AND CLOVE EXTRACTS AGAINST SUNFLOWER SEEDS BLACK ROT DISEASE CAUSED BY ASPERGILLUS SPP.
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Publication Date
Mon Aug 30 2021
Journal Name
Al-kindy College Medical Journal
Clinical Course and Disease`s Outcome Aspects of COVID-19 Pediatric Patients in Ibn Al-Khateeb Isolation Hospital
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Background: Corona virus disease 2019 (COVID-19) is a communicable disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). It was first identified in December 2019 in Wuhan, China, and has since spread globally, leading to an ongoing pandemic.

Aim of study: to review the clinical, lab investigation and imaging techniques, in pediatric age group affected COVID-19 to help medical experts better understand and supply timely diagnosis and treatment.

Subjects and methods: this study is a retrospective descriptive clinical study. The medical records of patients were analyzed. Information’s recorded include demographic data, exposure history, symptoms, signs, laboratory findin

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Publication Date
Tue Feb 27 2024
Journal Name
Mathematical Modelling Of Engineering Problems
Dynamics of a Fractional-Order Prey-Predator Model with Fear Effect and Harvesting
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Publication Date
Mon Jul 01 2024
Journal Name
Journal Of Engineering
Design and Implementation of a Microstrip Six-Port Reflectometer (SPR) with Enhanced Bandwidth
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A compact microstrip six-port reflectometer (SPR) with extended bandwidth is proposed in this paper. The design is based on using 16-dB multi-section coupled line directional couplers and a multi-section 3-dB Wilkinson power divider operating from 1 to 6 GHz. The proposed SPR employs only two calibration standards: a matched load and an open load. As compared to other dielectric substrates, fabricating the proposed SPR involves using a low-cost (FR4) substrate. A novel algorithm is also proposed to estimate the complex reflection coefficient over the frequency ranges at which the standard performance of the circuit components is not fully satisfied. The new algorithm is based on the circles’ intersection points, which have been de

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Publication Date
Thu Jun 27 2024
Journal Name
Malaysian Journal Of Mathematical Sciences
Dynamics of a Social Model for Marriage and Divorce Relationship with Fear Effect
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The objective of this article is to delve into the intricate dynamics of marriage relationships, exploring the impact of emotions such as fear, love, financial considerations and likability. In our investigation, we adopt a perspective that acknowledges the nonlinear nature of interactions among individuals. Diverging from certain prior studies, we propose that the fear element within the context of marriage is not a singular, isolated factor but rather a manifestation resulting from the amalgamation of numerous social issues. This, in turn, contributes to the emergence of strained and unsuccessful relationships. Unlike conventional approaches, we extensively examine the conditions essential for the existence of all socially signifi

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Publication Date
Wed Oct 17 2018
Journal Name
Journal Of Economics And Administrative Sciences
The impact of the "Senge" Model of Organizational Learning in the adoption of Total Quality Management principles) Exploratory study in an organization)
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      This study is concerned with organizational learning and its impact on total quality management in the education sector. Organizational learning is a process that provides the educational sector with the ability to adapt and respond rapidly to developments and changes in a better way according to its main dimensions (Mental Models, Personal Mastery, Team Learning, Shared Vision, System Thinking) by adopting the philosophy of Total Quality Management (TQM) in accordance with its basic dimensions (leadership, customer satisfaction, participation of workers, continuous improvement, training and education). The main purpose of this study is to know (the impact of the Senge model of organizational learni

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Publication Date
Wed Oct 17 2018
Journal Name
Journal Of Economics And Administrative Sciences
The impact of the "Senge" Model of Organizational Learning in the adoption of Total Quality Management principles) Exploratory study in an organization)
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      This study is concerned with organizational learning and its impact on total quality management in the education sector. Organizational learning is a process that provides the educational sector with the ability to adapt and respond rapidly to developments and changes in a better way according to its main dimensions (Mental Models, Personal Mastery, Team Learning, Shared Vision, System Thinking) by adopting the philosophy of Total Quality Management (TQM) in accordance with its basic dimensions (leadership, customer satisfaction, participation of workers, continuous improvement, training and education). The main purpose of this study is to know (the impact of the Senge model of organizational learni

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Publication Date
Sat Aug 01 2020
Journal Name
Heat Transfer
A parametric study of a photovoltaic panel with cylindrical fins under still and moving air conditions in Iraq
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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
Hybrid CNN-based Recommendation System
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Recommendation systems are now being used to address the problem of excess information in several sectors such as entertainment, social networking, and e-commerce. Although conventional methods to recommendation systems have achieved significant success in providing item suggestions, they still face many challenges, including the cold start problem and data sparsity. Numerous recommendation models have been created in order to address these difficulties. Nevertheless, including user or item-specific information has the potential to enhance the performance of recommendations. The ConvFM model is a novel convolutional neural network architecture that combines the capabilities of deep learning for feature extraction with the effectiveness o

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