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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 Apr 01 2019
Journal Name
Iraqi Journal Of Biotechnology
The Promising Anti-Tumor Impact of Newcastle Disease Virus Expressing IL-2 and P53 Genes in Many Cancer Cell Lines In vitro
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Abstract: Recombinant Newcastle disease virus (rNDV) has shown an anticancer effect in preclinical studies, but has never been tested in a lung cancer models. In this study we explored the anticancer activity of genetically modified NDV expressing IL-2-P53 (rClone30–IL-2-P53) in lung cancer model. We have cloned IL-2 and P53 genes and inserted them in the viral genome of New Castle Disease Virus to create a genetically modified rNDV- IL-2-P53 virus and tested the anti-tumor activity of the new virus in vitro on different types of cancer cell lines by MTT assay. TheIL-2 and P53 gene were successfully cloned and inserted into the viral genome by using a Mlu I and Sfi I endonucleases, viral vector was constructed correctly and successf

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Publication Date
Wed Mar 18 2020
Journal Name
Baghdad Science Journal
Identification of Cladosporium sp. Fungi by in- silico RFLP-PCR
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Cladosporium sp. plays an important role in human health, it is one of the pathogenic fungi which cause allergy and asthma and most frequently isolated from airborne spores.  In this study, a couple of universal PCR primers were designed to identify the pathogenic fungi Cladosporium sp. according to conserved region 5.8S, 18S and 28S subunit ribosomal RNA gene in Cladosporium species. In silico RFLP-PCR were used to identify twenty-four Cladosporium strains. The results showed that the universal primer has the specificity to amplify the conserved region in 24 species as a band in virtual agarose gel. They also showed that the RFLP method is able to identify three Cladosporium spe

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Publication Date
Sun Jul 06 2014
Journal Name
Journal Of Educational And Psychological Researches
الممارسات التدريسية لتدريسي أقسام كليات التربية جامعة بغداد في ضوء دوافع التعلم
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Find aimed to reveal the teaching practices of the teaching faculties of education departments of the University of Baghdad in the light of the motives of learning from the perspective of students . Researcher selected the research community in a deliberate humanitarian sections of students and faculties of education for girls and IbnRushd . Ed reached basic research sample ( 400 ) students were numbers search tool questionnaire , and included (30) paragraph . In processors statistical data , use the weighted average and the weight percentile , results have shown that it is more paragraphs which received wide acceptance from the viewpoint of students ( do not make fun of the students' answers wrong but corrects and discussed with them )

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Publication Date
Thu Jan 22 2026
Journal Name
Journal Of Advanced Research Design
Sustainable Leaf Plant Disease Based on Salp Swarm Algorithm for Feature Selection
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Sustainable plant protection and the economy of plant crops worldwide depend heavily on the health of agriculture. In the modern world, one of the main factors influencing economic growth is the quality of agricultural produce. The need for future crop protection and production is growing as disease-affected plants have caused considerable agricultural losses in several crop categories. The crop yield must be increased while preserving food quality and security and having the most negligible negative environmental impact. To overcome these obstacles, early discovery of satisfactory plants is critical. The use of Advances in Intelligent Systems and information computer science effectively helps find more efficient and low-cost solutions. Thi

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Publication Date
Fri Jun 30 2023
Journal Name
Iraqi Geological Journal
Integrated Core and Log Data to Determine the Reservoir Flow Unit and Rock Facies for Mishrif Formation in South Eastern Iraq
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This work represents study the rock facies and flow unit classification for the Mishrif carbonate reservoir in Buzurgan oil Field, which located n the south eastern Iraq, using wire line logs, core samples and petrophysical data (log porosity and core permeability). Hydraulic flow units were identified using flow zone indicator approach and assessed within each rock type to reach better understanding of the controlling role of pore types and geometry in reservoir quality variations. Additionally, distribution of sedimentary facies and Rock Fabric Number along with porosity and permeability was analyzed in three wells (BU-1, BU-2, and BU-3). The interactive Petrophysics - IP software is used to assess the rock fabric number, flow zon

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Publication Date
Fri Dec 01 2023
Journal Name
Case Studies In Chemical And Environmental Engineering
Removal of copper from a simulated wastewater by electromembrane extraction technique using a novel electrolytic cell provided with a flat polypropylene membrane infused with 1-octanol and DEHP as a carrier
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Publication Date
Sun Jan 01 2017
Journal Name
البحوث التربوية والنفسية
the effect of an educational -learning programe according to the concepts of renewable energy and nanotechnology on technological enlightenment among students of the che chemistry department
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Publication Date
Fri Apr 12 2019
Journal Name
Journal Of Economics And Administrative Sciences
Measuring and analysis of the impact of public budget deficit on external debt in lraq with in the framework of joint integration of the period (1990 – 2016 )
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The concept of deficit in public budget becomes a chronic economic phenomenon in most of the world, whether the advanced countries or developing countries. Despite  the difference in the visions of the economic schools to accept or reject the deficit in public budget but the opinion that prevailed is the necessity of the state to reduce the public spending which led to a continuous deficits in the public budget which consequently increased the government borrowing ,increase income taxes and wealth, consequently this weakened the in motivation in private investment which contributed to the increase of in factionary stagnation , so that governments have to cover the lack of local funding sources which become difficult to be eq

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Publication Date
Mon Apr 01 2024
Journal Name
Telkomnika (telecommunication Computing Electronics And Control)
Classification of grapevine leaves images using VGG-16 and VGG-19 deep learning nets
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The successful implementation of deep learning nets opens up possibilities for various applications in viticulture, including disease detection, plant health monitoring, and grapevine variety identification. With the progressive advancements in the domain of deep learning, further advancements and refinements in the models and datasets can be expected, potentially leading to even more accurate and efficient classification systems for grapevine leaves and beyond. Overall, this research provides valuable insights into the potential of deep learning for agricultural applications and paves the way for future studies in this domain. This work employs a convolutional neural network (CNN)-based architecture to perform grapevine leaf image classifi

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Publication Date
Thu Aug 28 2025
Journal Name
Tikrit Journal Of Engineering Sciences
Influence of High Temperatures on the Mechanical Properties of GFRP Pultruded Sections- Review
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The application of pultruded (GFRP) composite has become increasingly prominent in civil infrastructure projects. This study provides a comprehensive analysis of experimental and numerical studies conducted on the mechanical characteristics of (GFRP) composites across various temperature conditions, encompassing ambient and fire scenarios. The compilation comprises over 100 scholarly articles that examine the mechanical behavior of (GFRP) materials, specifically emphasizing their tensile and compressive strengths, showed the mechanical properties of (GFRP) materials are commonly compromised when exposed to high temperatures that approach or surpass the resin's glass transition temperature (Tg). In contrast, temperatures that are low

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