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bsj-8544
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
Fri Sep 30 2022
Journal Name
International Journal Of Health Sciences
Relation of retinol binding protein4, visfatin and vitamin a in obese and non obese Iraqi patients with non alcoholic fatty liver disease
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One of the most common public liver diseases over the world is fatty liver which contain alcoholic and non-alcoholic fatty liver. One-fourth among general population are impact Non-Alcoholic Fatty Liver Disease (NAFLD) in the worldwide.Retinol binding protein 4 (RBP4) is known as an adipokine, mainly synthesized and secreted from the liver and form adipose tissues. RBP4 acts as a transporter and specifically bound to retinol from liver to others tissues. Visfatin is an adipocytokine and mainly produced from visceral fat tissue, skeletal muscles as well as liver. Vitamin A absorbed, transported as retinyl esters to the liver then hydrolyzed to the retinol form and storage in hepatic stellate cells (HSCs) after reesterified with rigly

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Publication Date
Thu Jun 01 2023
Journal Name
Baghdad Science Journal
Mn(II),Fe(III),Co(II)and Rh(III) complexes with azo ligand: Synthesis, characterization, thermal analysis and bioactivity
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New series of metal ions complexes have been prepared from the new ligand [4-Amino-N-(5-methyl-isaxazol-3-yl)-benzenesulfonamide] derived from Sulfamethoxazole and 3-aminophenol. Accordingly, mono-nuclear Mn(II), Fe(III), Co (II), and Rh(III) complexes were prepared by the reaction of previous ligand with MnCl2.4H2O, CoCl2.6H2O, FeCl3.6H2O and RhCl3H2O, respectively. The compounds have been characterized by Fourier-transform infrared (FTIR), ultraviolet–visible (UV–vis), mass,  1H-, and 13C-nuclear magnetic resonance (NMR) spectra and thermo gravimetric analysis (TGA& DSC) curve, Bohr magnetic (B.M.), elemental microanal

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Publication Date
Fri Jan 01 2016
Journal Name
Journal Of Sensors
WDARS: A Weighted Data Aggregation Routing Strategy with Minimum Link Cost in Event-Driven WSNs
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Realizing the full potential of wireless sensor networks (WSNs) highlights many design issues, particularly the trade-offs concerning multiple conflicting improvements such as maximizing the route overlapping for efficient data aggregation and minimizing the total link cost. While the issues of data aggregation routing protocols and link cost function in a WSNs have been comprehensively considered in the literature, a trade-off improvement between these two has not yet been addressed. In this paper, a comprehensive weight for trade-off between different objectives has been employed, the so-called weighted data aggregation routing strategy (WDARS) which aims to maximize the overlap routes for efficient data aggregation and link cost

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Publication Date
Sat Jun 15 2024
Journal Name
Obstetrics & Gynaecology Forum
THE ROLE OF FUNGAL INFECTIONS IN THE PATHOGENESIS OF DIALYSIS-DEPENDENT AND NON-DIALYSIS-DEPENDENT PATIENTS WITH KIDNEY DISEASE
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Abstract The results of isolation, morphological and microscopic diagnosis, Chromic Agar, Vitik technology and Bact Alert showed that the diagnosis of fungi isolated from blood samples of end-stage renal patients who did not undergo dialysis and those who underwent dialysis was 60 samples for each type. The total number of fungal isolates isolated from people who did not undergo dialysis was 26 pathogenic fungal isolates, with a percentage frequency of 43.33%. In this study, 4 genera of pathogenic fungi were identified: Candida spp, Rhodotorula spp, Cryptococcus spp. and Aspergillus spp. The number of Candida isolates reached 13 isolates, with a frequency of 50%. The results also showed that the diagnosed species from the genus Rhodotorula

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Publication Date
Thu Jan 11 2024
Journal Name
Research Square
Exploring the Potential of Terrestrial Isopoda, Porcellionides cingendus, for Assessing Environmental Sustainability
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Abstract<p><bold>Introduction:</bold> Environmental sustainability is crucial for maintaining diverse and productive biological systems. Terrestrial isopods, such as Porcellionides cingendus, are known for their environmentally friendly characteristics and adaptability. This study explores the potential of <italic>P. cingendus</italic> in improving environmental sustainability. <bold>Methods:</bold> Samples of P. cingendus were collected from various locations and reared in controlled environments. Waste consumption efficiency was evaluated by measuring the consumption of various cellulosic wastes over 15 days. Statistical analysis was performed using One-Way ANOVA. <jat></jat></p> ... Show More
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Publication Date
Thu Dec 31 2015
Journal Name
Al-khwarizmi Engineering Journal
Prediction of Performance Equations for Household Compressors Depending on Manufacturing Data for Refrigerators and Freezers
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Abstract

 A surface fitting model is developed based on calorimeter data for two famous brands of household compressors. Correlation equations of ten coefficient polynomials were found as a function of refrigerant saturating and evaporating temperatures in range of (-35℃ to -10℃) using Matlab software for cooling capacity, power consumption, and refrigerant mass flow rate.

Additional correlations equations for these variables as a quick choice selection for a proper compressor use at ASHRAE standard that cover a range of swept volume range (2.24-11.15) cm3.

The result indicated that these surface fitting models are accurate with in ± 15% for 72 compressors model of cooling cap

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Publication Date
Sun Mar 15 2020
Journal Name
Journal Of The College Of Education For Women
The Degree of Using Computers in Administrative Jobs and the Obstacles of Usage in Public Education Schools in Sharoorah Governorate: Saudi Arabia
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This study aimed to identify the degree of use computers in administrative functions (planning, organization, controlling, and evaluation) among school leaders and assistants in public education schools in Sharoorah governorate ، as well as to identify obstacles of  use computers in administrative functions from the perspective of school leaders and assistants male and female in public schools during the academic year 1439-1440, the study sample  (66) school leaders and assistants, males (58), a and females (44), , and to answer the questions of the study, the researchers developed a questionnaire consisting of  (60) items, has been verified sincerity and persistence, and data analysis was used frequencies, percentages an

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Publication Date
Thu Jun 01 2017
Journal Name
Journal Of The College Of Languages (jcl)
The Effect of Teaching English Vocabulary Learning Strategies on Iraqi Intermediate School Students’ Vocabulary Performance and Reading Comprehension
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The present study aims at empirically investigating the effect of vocabulary learning strategies on Iraqi intermediate school students’vocabulary performance and reading comprehension. The population of the present study includes all the 1st year male students of  Al-Wark’a intermediate  school of Al-Risafa 1/ General  Directorate of Education for the first course of the academic year (2015-2016). To achieve the aim of the study ,a pre-test and post-test after (5) weeks of experiment are administrated .The sample of the present study consists of (100) subjects :(50) students as an experimental group and other (50) students as  a control group . The subj

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Publication Date
Tue Jan 01 2019
Journal Name
Advances On Computational Intelligence In Energy
A Theoretical Framework for Big Data Analytics Based on Computational Intelligent Algorithms with the Potential to Reduce Energy Consumption
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Within the framework of big data, energy issues are highly significant. Despite the significance of energy, theoretical studies focusing primarily on the issue of energy within big data analytics in relation to computational intelligent algorithms are scarce. The purpose of this study is to explore the theoretical aspects of energy issues in big data analytics in relation to computational intelligent algorithms since this is critical in exploring the emperica aspects of big data. In this chapter, we present a theoretical study of energy issues related to applications of computational intelligent algorithms in big data analytics. This work highlights that big data analytics using computational intelligent algorithms generates a very high amo

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Publication Date
Thu Dec 01 2022
Journal Name
Iraqi Journal Of Statistical Sciences
Use the robust RFCH method with a polychoric correlation matrix in structural equation modeling When you are ordinal data
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