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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 Nov 01 2020
Journal Name
Iop Conference Series: Materials Science And Engineering
Development of an Optimized Botnet Detection Framework based on Filters of Features and Machine Learning Classifiers using CICIDS2017 Dataset
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Abstract<p>Botnet is a malicious activity that tries to disrupt traffic of service in a server or network and causes great harm to the network. In modern years, Botnets became one of the threads that constantly evolving. IDS (intrusion detection system) is one type of solutions used to detect anomalies of networks and played an increasing role in the computer security and information systems. It follows different events in computer to decide to occur an intrusion or not, and it used to build a strategic decision for security purposes. The current paper <italic>suggests</italic> a hybrid detection Botnet model using machine learning approach, performed and analyzed to detect Botnet atta</p> ... Show More
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Publication Date
Wed Dec 15 2021
Journal Name
Arab World English Journal
Aggressive Language in Literature: A Pragmatic Approach
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Aggression is a negative form of an anti-social behavior. It is produced because of a particular reason, desire, want, need, or due to the psychological state of the aggressor. It injures others physically or psychologically. Aggressive behaviors in human interactions cause discomfort and disharmony among interlocutors. The paper aims to identify how aggressive language manifests itself in the data under scrutiny in terms of the pragmatic paradigm. Two British literary works are the data; namely, Look Back in Anger by John Osborne (1956), and The Birthday Party by Harold Pinter (1957). This paper endeavors to answer the question of how aggressive language is represented in literature pragmatically? It is hoped to be significant to

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Publication Date
Sat Nov 04 2023
Journal Name
Russian Journal Of General Chemistry
Synthesis and Characterization of Metals Complexes with Uracil and Uracil Derivatives (A Review)
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Previous studies on the synthesis and characterization of metal chelates with uracil by elemental analysis, conductivity, IR, UV-Vis, NMR spectroscopy, and thermal analysis were covered in this review article. Reviewing these studies, we found that uracil can be coordinated through the electron pair on the N1, N3, O2, or O4 atoms. If the uracil was a mono-dentate ligand, it will be coordinated by one of the following atoms: N1, N3 or O2. But if the uracil was bi-dentate ligand, it will be coordinated by atoms N1 and O2, N3 and O2 or N3 and O4. However, when uracil forms complexes in the form of polymers, coordination occurs through the following atoms: N1 and N3 or N1 and O4.

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Publication Date
Sat Apr 01 2023
Journal Name
Russian Journal Of General Chemistry
Synthesis and Characterization of Metals Complexes with Uracil and Uracil Derivatives (A Review)
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Publication Date
Sun Mar 31 2024
Journal Name
Iraqi Geological Journal
Permeability Prediction and Facies Distribution for Yamama Reservoir in Faihaa Oil Field: Role of Machine Learning and Cluster Analysis Approach
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Empirical and statistical methodologies have been established to acquire accurate permeability identification and reservoir characterization, based on the rock type and reservoir performance. The identification of rock facies is usually done by either using core analysis to visually interpret lithofacies or indirectly based on well-log data. The use of well-log data for traditional facies prediction is characterized by uncertainties and can be time-consuming, particularly when working with large datasets. Thus, Machine Learning can be used to predict patterns more efficiently when applied to large data. Taking into account the electrofacies distribution, this work was conducted to predict permeability for the four wells, FH1, FH2, F

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Publication Date
Tue Nov 06 2018
Journal Name
Iraqi National Journal Of Nursing Specialties
Correlation between Thyroid-related Hormones and Preeclampsia
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Objectives: In order to highlight the TSH and thyroid hormones levels in preeclamptic and healthy pregnant
women.
Methodology: Ninety patients with preeclampsia were divided into two groups according to the severity of
disease; those with mild disease (37 patients) and those with a severe form (53 patients). A separate group of 30
normal women were included as a normal control group. Venus blood samples were collected from all groups
and the serum was obtained for hormone analysis by ELISA test. Results are expressed using SPSS for window
version 11.0.
Results: Mean serum TSH levels were significantly increased in both of mild and severe preeclampsia compared
with normal pregnancy, and T3 serum level showed a sign

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Publication Date
Sun Feb 03 2019
Journal Name
Journal Of The College Of Education For Women
Cleopatra between the western and Arabic literature
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Publication Date
Fri Jul 01 2022
Journal Name
Iop Conference Series: Earth And Environmental Science
A study Some Technical Indicators of the Local Designed Machine
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Abstract<p>The effect of compound machine on wheat/ AlNoor cultivar was studied based on some technical indicators. were tested under three speeds ( 2.541, 3.433 and 4.091km.hr<sup>-1</sup>) and three tillage depths (14, 16 and 18cm). The experiments were conducted in a factorial experiment under complete randomized design with three replications. The results showed that the 2.541km.hr<sup>-1</sup> practical speed was significantly better than other two speed in all studied conditions. Except for the FC, which achieved the best results with the third speed 4.091 km.hr<sup>-1</sup>. mechanical parameters, plant growth parameters and yield and growth parameters. The 1</p> ... Show More
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Publication Date
Fri Dec 01 2023
Journal Name
Political Sciences Journal
Exploring the Effects of European Union Conditionality Language on European Mediterranean Human Rights Dialogue
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Since more than a decade, human rights dialogue in the European Mediterranean Region has been marked by a number of tensions. Although a number of factors contribute to such disputes, the effect of human rights conditionality, which ties EU economic cooperation progression with partner countries human rights advancement, on the dialogue has not been studied. Understanding the aspects, impacts, and effects of conditionality on Euro-Med relations is crucial for furthering dialogue. Yet this variable has been almost entirely neglected in academic and policy research. The research concludes several direct and indirect impacts of conditionality on human rights dialogue using a mixed methodology approach. Direct effects are reflected in the wi

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Publication Date
Wed Jan 30 2013
Journal Name
Al-kindy College Medical Journal
Using the Abbreviated Version of Modification of Diet in Renal Disease Formula as A Primary Estimate for the Prevalence of Undiagnosed Chronic Kidney Disease in Patients with Acute Stroke
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Introduction: The association between acute stroke and
renal function is well known. The aim of this study is to
know which group of patients with acute stroke is more
likely to have undiagnosed Chronic Kidney Disease and
which risk factors are more likely to be associated with.
Methods:We studied 77 patients who were diagnosed to
have an acute stroke.Patients were selected between
April2011andJune 2011 using the " 4-variable
Modification of
Diet in Renal Disease Formula " which estimates
Glomerular Filtration Rate using four variables :serum
creatinine ,age ,race and gender.
Results :The study included 38 male and 39 females
patients ,aged (35-95) years. Glomerular Filtration Rate in
patients wi

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