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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
Mon Jan 01 2024
Journal Name
Journal Of Business, Communication & Technology
Exploring the Adoption of Big Data Analytics in the Oil and Gas Industry: A Case Study
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The oil and gas industry relies heavily on IT innovations to manage business processes, but the exponential generation of data has led to concerns about processing big data, generating valuable insights, and making timely decisions. Many companies have adopted Big Data Analytics (BDA) solutions to address these challenges. However, determining the adoption of BDA solutions requires a thorough understanding of the contextual factors influencing these decisions. This research explores these factors using a new Technology-Organisation-Environment (TOE) framework, presenting technological, organisational, and environmental factors. The study used a Delphi research method and seven heterogeneous panelists from an Oman oil and gas company

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Publication Date
Sat Jan 08 2022
Journal Name
Arab Scientific Heritage Journal
Weights of the Tawshih art (review)
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This study presented more than twenty books that dealt with the subject of (Weights of the Tawshih art), whether their study was independent and dedicated the art of Tawshih as a part of book. Therefore, the review of the sources and references on the art of the Tawshih is not specific for place or time, it was a broad and comprehensive review of all the places where the muwashahat appeared in the east and west, Andalusia was one of the most important areas covered by the study arbic Maghreb and Iraq. The art of tawshih took different forms according to the countries in which they appeared. Muwashahat is a new art that appeared in Andalusia, its main goal was to renew the Khalilian weights and to find the poetic rhythm that fits with the so

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Publication Date
Tue Oct 08 2024
Journal Name
Cureus
Orbital Langerhans Cell Histiocytosis: A Systematic Review of 228 Cases
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Publication Date
Thu Oct 29 2020
Journal Name
Complexity
Training and Testing Data Division Influence on Hybrid Machine Learning Model Process: Application of River Flow Forecasting
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The hydrological process has a dynamic nature characterised by randomness and complex phenomena. The application of machine learning (ML) models in forecasting river flow has grown rapidly. This is owing to their capacity to simulate the complex phenomena associated with hydrological and environmental processes. Four different ML models were developed for river flow forecasting located in semiarid region, Iraq. The effectiveness of data division influence on the ML models process was investigated. Three data division modeling scenarios were inspected including 70%–30%, 80%–20, and 90%–10%. Several statistical indicators are computed to verify the performance of the models. The results revealed the potential of the hybridized s

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Publication Date
Sat Oct 01 2022
Journal Name
Alexandria Engineering Journal
A review of free piston engine control literature—Taxonomy and techniques
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Publication Date
Thu Dec 15 2022
Journal Name
Journal Of Baghdad College Of Dentistry
Force degradation of orthodontic elastomeric chains: A literature review
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Background: Elastomeric chains are used to generate force in many orthodontic procedures, but this force decays over time, which could affect tooth movement. This study aimed to study the force degradation of elastomeric chains. Data and Sources: An electronic search on Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, LILACS, and PubMed was made, only articles written in English were included, up to January 2022.Study selection: Fifty original articles, systematic reviews, and RCTs were selected. Conclusion: Tooth movement, salivary enzymes, alcohol-containing mouthwash, whitening mouthwash, and alkaline and strong acidic (pH <5.4) solutions all have a significant impact on elastomeric chain force degradation. The fo

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Publication Date
Thu Dec 15 2022
Journal Name
Journal Of Baghdad College Of Dentistry
Force degradation of orthodontic elastomeric chains: A literature review
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Background: Elastomeric chains are used to generate force in many orthodontic procedures, but this force decays over time, which could affect tooth movement. This study aimed to study the force degradation of elastomeric chains. Data and Sources: An electronic search on Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, LILACS, and PubMed was made, only articles written in English were included, up to January 2022.Study selection: Fifty original articles, systematic reviews, and RCTs were selected. Conclusion: Tooth movement, salivary enzymes, alcohol-containing mouthwash, whitening mouthwash, and alkaline and strong acidic (pH <5.4) solutions all have a significant impact on elastomeric chain force degradation. T

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Publication Date
Sat Aug 01 2020
Journal Name
Surgical Neurology International
Unilateral absence of the internal carotid artery associated with anterior communicating artery aneurysms: Systematic review and a proposed management algorithm
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Background:

Absence or hypoplasia of the internal carotid artery (ICA) is a rare congenital anomaly that is mostly unilateral and highly associated with other intracranial vascular anomalies, of which saccular aneurysm is the most common. Blood flow to the circulation of the affected side is maintained by collateral pathways, some of which include the anterior communicating artery (Acom) as part of their anatomy. Therefore, temporary clipping during microsurgery on Acom aneurysms in patients with unilateral ICA anomalies could jeopardize these collaterals and place the patient at risk of ischemic damage. In this paper, we review the literature on cases with a unilaterally absent ICA associa

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Publication Date
Wed Apr 02 2014
Journal Name
Journal Of Theoretical And Applied Information Technology
TUMOR BRAIN DETECTION THROUGH MR IMAGES: A REVIEW OF LITERATURE
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Today’s modern medical imaging research faces the challenge of detecting brain tumor through Magnetic Resonance Images (MRI). Normally, to produce images of soft tissue of human body, MRI images are used by experts. It is used for analysis of human organs to replace surgery. For brain tumor detection, image segmentation is required. For this purpose, the brain is partitioned into two distinct regions. This is considered to be one of the most important but difficult part of the process of detecting brain tumor. Hence, it is highly necessary that segmentation of the MRI images must be done accurately before asking the computer to do the exact diagnosis. Earlier, a variety of algorithms were developed for segmentation of MRI images by usin

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Publication Date
Sun Jun 30 2024
Journal Name
Tikrit Journal For Dental Sciences
Aligning Archwires in Orthodontics: Exploring the Past, Present, and Future - A Comprehensive Narrative Review
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Orthodontic wires facilitate the required dental adjustments in the context of orthodontic therapy. The archwire has played a crucial role in orthodontic treatment, and the increasing emphasis on aesthetic preferences from patients, as well as the development of composite and ceramic brackets, have prompted investigations into aesthetic archwires that complement these brackets. Orthodontic wires are produced using a diverse range of materials. The utilisation of all available wire types can improve patient comfort, decrease chairside time, and shorten the overall duration of treatment. The individual clinician must possess comprehensive knowledge and comprehension of the various requirements and alternatives throughout the therapeut

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