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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
Thu Dec 21 2023
Journal Name
Mathematical Modelling Of Engineering Problems
Enhancing Spatial Accuracy of OpenStreetMap Data: A Geometric Approach
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OpenStreetMap (OSM), recognised for its current and readily accessible spatial database, frequently serves regions lacking precise data at the necessary granularity. Global collaboration among OSM contributors presents challenges to data quality and uniformity, exacerbated by the sheer volume of input and indistinct data annotation protocols. This study presents a methodological improvement in the spatial accuracy of OSM datasets centred over Baghdad, Iraq, utilising data derived from OSM services and satellite imagery. An analytical focus was placed on two geometric correction methods: a two-dimensional polynomial affine transformation and a two-dimensional polynomial conformal transformation. The former involves twelve coefficients for ad

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Publication Date
Sun Oct 05 2025
Journal Name
Journal Of Studies And Researches Of Sport Education
The impact of the V-shape strategy on learning basic skills in a breaststroke
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Publication Date
Mon Jan 01 2018
Journal Name
International Journal Of Surgery Open
Incidence of differentiated thyroid carcinoma in multinodular goiter patients
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Publication Date
Tue Jan 01 2019
Journal Name
Biochemical & Cellular Archives
Assessment of uric acid in patients of end-stage renal disease with hypertension and diabetic nephropathy and the risk of cardiovascular diseases
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The relationship of hyperuricemia to kidney disease, diabetes, hypertension and the risk of cardiovascular diseases remain controversial. The aim of this study is to evaluate the use of uric acid (UA) levels to find the higher risk of cardiovascular disease (CVD) in patients with end stage renal disease that have diabetic nephropathy (DN), nephropathy with hypertension (NH) and patients with both diabetic nephropathy with hypertension (DNH). This study deals with 115 patients with end-stage renal disease under hemodialysis sub-grouped into 35 patients with (DN), 40 patients with (NH), and 40 patients with (DNH). Some biochemical parameters were determined in the serum of all participants such as HbA1c, fasting blood glucose (FBG), UA, urea,

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Publication Date
Fri May 03 2024
Journal Name
Doklady Biochemistry And Biophysics
Superoxide Dismutase and Clopidogrel: A Potential Role in Peripheral Arterial Disease Treatment
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Oxidative stress plays a crucial role in the pathogenesis of peripheral artery disease (PAD). This study aimed to investigate the effect of clopidogrel on oxidative stress in PAD patients. Seventy subjects were divided into three groups: PAD patients before treatment (B-PAD), PAD patients after treatment with clopidogrel (A-PAD), and healthy controls. Serum levels of superoxide dismutase (SOD), copper (Cu), zinc (Zn), manganese (Mn), and oxidized protein were measured. SOD activities were also determined. The results showed that SOD activities, and SOD specific activities were significantly decreased in PAD patients compared to healthy individuals. After treatment with clopidogrel, SOD activities, and SOD specific activities were continuous

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Publication Date
Mon Aug 01 2016
Journal Name
2016 38th Annual International Conference Of The Ieee Engineering In Medicine And Biology Society (embc)
Changes in the EEG amplitude as a biomarker for early detection of Alzheimer's disease
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The rapid increase in the number of older people with Alzheimer's disease (AD) and other forms of dementia represents one of the major challenges to the health and social care systems. Early detection of AD makes it possible for patients to access appropriate services and to benefit from new treatments and therapies, as and when they become available. The onset of AD starts many years before the clinical symptoms become clear. A biomarker that can measure the brain changes in this period would be useful for early diagnosis of AD. Potentially, the electroencephalogram (EEG) can play a valuable role in early detection of AD. Damage in the brain due to AD leads to changes in the information processing activity of the brain and the EEG which ca

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Publication Date
Sat Dec 21 2024
Journal Name
Gastroenterology
Evaluation of global DNA methylation, homocysteine and vitamin B12 levels among patients with celiac disease
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Celiac disease (CD) is an immune-mediated disorder caused by gluten in genetically susceptible individuals characterized by chronic inflammation that essentially affects the small intestine. Objective: this study was designed to measure the potential role of some serological biomarkers including vitamin B12 and homocysteine (HCY) in the progression of CD as well as their relations to global DNA methylation (5mC). Materials and methods. Forty CD patients were enrolled in the study with an average age of (36.60 ± 2.03) years (range between 15 and 60). The diagnosis of the disease was confirmed by serological examinations and intestinal endoscopy in Gastroenterology and Liver Teaching Hospital in the Medical City Hospital in Baghdad

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Publication Date
Thu Jun 30 2011
Journal Name
Al-kindy College Medical Journal
Prevalence of clinically significant Hepatopulmonary Syndrome among Patients with Chronic Liver Disease and Portal Hypertension
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Background : The hepatopulmonary syndrome (HPS) is defined as the triad of liver disease, arterial deoxygenation, and pulmonary vascular dilatation. The reported prevalence of HPS in cirrhotic patients varies between 5% -17.5%.Objective : To estimate the prevalence of hepatopulmonary syndrome among patients with chronic liver disease and portal hypertension and to study the correlation between HPS and the severity of liver disease.Patients and methods : Thirty patients were studied for the presence of HPS using transthoracic contrast echocardiography for detection of pulmonary vasodilatation. Arterial oxygen saturation (SaO2) was determined in erect and supine position using a pulse oximeter , (SaO2 ≤ 92 % in supine position and/or a d

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Publication Date
Thu Oct 01 2015
Journal Name
Journal Of Economics And Administrative Sciences
Estimation Multivariate data points in spatial statistics with application
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This paper  deals  to how to estimate points non measured spatial data when the number of its terms (sample spatial) a few, that are not preferred for the estimation process, because we also know that whenever if the data is large, the estimation results of the points non measured to be better and thus the variance estimate less, so the idea of this paper is how to take advantage of the data other secondary (auxiliary), which have a strong correlation with the primary data (basic) to be estimated single points of non-measured, as well as measuring the variance estimate, has been the use of technique Co-kriging in this field to build predictions spatial estimation process, and then we applied this idea to real data in th

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Publication Date
Tue Dec 01 2020
Journal Name
Gulf Economist
The Bayesian Estimation in Competing Risks Analysis for Discrete Survival Data under Dynamic Methodology with Application to Dialysis Patients in Basra/ Iraq
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Survival analysis is one of the types of data analysis that describes the time period until the occurrence of an event of interest such as death or other events of importance in determining what will happen to the phenomenon studied. There may be more than one endpoint for the event, in which case it is called Competing risks. The purpose of this research is to apply the dynamic approach in the analysis of discrete survival time in order to estimate the effect of covariates over time, as well as modeling the nonlinear relationship between the covariates and the discrete hazard function through the use of the multinomial logistic model and the multivariate Cox model. For the purpose of conducting the estimation process for both the discrete

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