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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
Sat Apr 01 2017
Journal Name
Journal Of Economics And Administrative Sciences
The diagnosis and determine the level of balance between the time available for life and work: The case study of a sample of doctors hospitals City of Medicine
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Purpose: The diagnosis and determine the level of balance between the time available for life and work with the doctors in the hospitals of t the six hospitals in the City of Medicine.

Design / methodology / Approach: It has been relying on ready-scale, to make sure the diagnosis and determine the level of balance between the time available for life and work, where they were distributed on Form 42 doctors in the six hospitals in the City of Medicine, were analyzed by software (Nvivo and SPSS v.22).

Results: The results showed that there is a good level of balance between the time available for life and work with the doctors.

Research limitations: The diffi

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Publication Date
Sat Jan 01 2022
Journal Name
Technologies And Materials For Renewable Energy, Environment And Sustainability: Tmrees21gr
Challenges facing the transition of traditional cities to smart: Studying the challenges faced by the transition of a traditional area such as Al-Kadhimiya city center to the smart style
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Challenges facing the transition of traditional cities to smart: Studying the challenges faced by the transition of a traditional area such as Al-Kadhimiya city center to the smart style

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Publication Date
Sat Feb 01 2025
Journal Name
Saudi Medical Journal
Spectrum and classification of ATP7B variants with clinical correlation in children with Wilson disease
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Publication Date
Thu Apr 01 2010
Journal Name
Journal Of Educational And Psychological Researches
The Academic and Practical Frames to The roles Of Systematic Education in the Social and Economic development
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Education in it s different levels becomes development in any country. There fore, nations pay great attention to educational systems, because they perceive that preparing human resources is essential to the development of these nations.
The present study deals with the a academic frames which formulate education in each educational system such as educational philosophy , educational aims , educational strategies by which the academic frames are carried out, which is limited to curriculum, teacher preparations, school activities, in addition to guidance and counseling.
This study reaches some conclusion which are derived from the description of the academic and practical frames some suggestion are made for the mechanism which facil

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Publication Date
Wed Sep 15 2021
Journal Name
Journal Of Baghdad College Of Dentistry
Diet and orthodontics- A review
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During the course of fixed orthodontic therapy, patients should be instructed to eat specific food stuffs and beverages in order to maintain good health for the dentition and supporting structures and prevent frequent attachment debonding that prolong the treatment duration. After searching and collecting articles from 1930 till July 2021, the current review was prepared to emphasize various types of foods that should be taken during the course of fixed orthodontic therapy and to explain the effect of various food stuffs and beverages on the growth and development of craniofacial structures, tooth surfaces, root resorption, tooth movement, retention and stability after orthodontic treatment and the effect on the components of fixed ortho

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Publication Date
Sat Feb 01 2025
Journal Name
Saudi Medical Journal
Spectrum and classification of<i>ATP7B</i>variants with clinical correlation in children with Wilson disease
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Objectives: To study the spectrum and classification of ATP7B variants in Iraqi children with Wilson disease by direct gene sequencing with clinical correlation. Methods: Fifty-five unrelated children with a clinical diagnosis of Wilson disease (WD) were recruited. Deoxyribonucleic acid was extracted from peripheral blood samples, and variants in the ATP7B gene were identified using next-generation sequencing. Results: Seventy-six deleterious variants were detected in 97 out of 110 alleles of the ATP7B gene. Thirty (54.5%) patients had 2 disease-causing variants (15 homozygous and 15 compound heterozygous). Twelve (21.8%) patients had one disease-causing variant and one variant of uncertain significance (VUS) with potential pathogenicity. T

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Publication Date
Mon Jun 14 2021
Journal Name
Biosense Dementia 2017 - International Workshop On Biosensors For Dementia From 13 – 14 June 2017 – Plymouth University, Plymouth, Uk
Changes in the Electroencephalogram as a Biomarker 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 because of a large number of people affected. 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, and to plan for the future. 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 caused to the brain due to AD leads t

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Publication Date
Wed Oct 21 2015
Journal Name
Integrated Journal Of Engineering Research And Technology
A HYBRID CUCKOO SEARCH AND BACK-PROPAGATION ALGORITHMS WITH DYNAMIC LEARNING RATE TO SPEED UP THE CONVERGENCE (SUBPL) ALGORITHM
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BP algorithm is the most widely used supervised training algorithms for multi-layered feedforward neural net works. However, BP takes long time to converge and quite sensitive to the initial weights of a network. In this paper, a modified cuckoo search algorithm is used to get the optimal set of initial weights that will be used by BP algorithm. And changing the value of BP learning rate to improve the error convergence. The performance of the proposed hybrid algorithm is compared with the stan dard BP using simple data sets. The simulation result show that the proposed algorithm has improved the BP training in terms of quick convergence of the solution depending on the slope of the error graph.

Publication Date
Fri Mar 18 2022
Journal Name
Aro-the Scientific Journal Of Koya University
Detecting Deepfakes with Deep Learning and Gabor Filters
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The proliferation of many editing programs based on artificial intelligence techniques has contributed to the emergence of deepfake technology. Deepfakes are committed to fabricating and falsifying facts by making a person do actions or say words that he never did or said. So that developing an algorithm for deepfakes detection is very important to discriminate real from fake media. Convolutional neural networks (CNNs) are among the most complex classifiers, but choosing the nature of the data fed to these networks is extremely important. For this reason, we capture fine texture details of input data frames using 16 Gabor filters indifferent directions and then feed them to a binary CNN classifier instead of using the red-green-blue

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Publication Date
Wed Jan 30 2013
Journal Name
Al-kindy College Medical Journal
Chronic Kidny Disease and Risk of coronary Artery Disease,Aprospective study
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AbstractBackground:Reduced glomeular filtration rate isassociated with increasedmorbidity in patientswith coronary arterydisease.Objectives :To analyze the declining eGFR andmortality risks in a patients with Chronic KidneyDisease and have had Coronary Artery Diseaseincluding risk factors .Patientsand Methods:The study included (160)patientsbetween the ages of 16 and 87years.Glomerular filtration rate was estimated (eGFR)using the Modification of Diet in Renal Diseaseequationand was categorized in the ranges<60 mL· min−1 per 1.73 m2and≥ 60 ml/min/1.73 m2.Baseline risk factors were analyzed by category ofeGFR,.The studied patients in emergencydepartment, were investigatedusing Coxproportional hazard models adjusting for traditiona

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