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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
Tue Dec 22 2020
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
Continuous improvement of technology and its role In reducing the costs in accordance with the management style On the basis of the activities (ABM): Applied Research in the General Company for Textile Industries / hula
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The administration on the basis of the activities designed to evaluate the performance of activities in terms of cost, time and quality by identifying activities that add value and those that are no add value and  enables the administration of making up their own continuous improvement in production, through lower costs and reduce the time and improve the quality   and reduce the incidence of spoilage and waste, y based search Ally premise that (the continuous improvement of the adoption of management style on the basis of the activities helps management in decision-making wise to reduce  costs) to prove the hypothesis has sought research to achieve its goal of  Alkadivh and Alkoppelan     &nb

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Publication Date
Sat Dec 30 2023
Journal Name
Journal Of Economics And Administrative Sciences
The Cluster Analysis by Using Nonparametric Cubic B-Spline Modeling for Longitudinal Data
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Longitudinal data is becoming increasingly common, especially in the medical and economic fields, and various methods have been analyzed and developed to analyze this type of data.

In this research, the focus was on compiling and analyzing this data, as cluster analysis plays an important role in identifying and grouping co-expressed subfiles over time and employing them on the nonparametric smoothing cubic B-spline model, which is characterized by providing continuous first and second derivatives, resulting in a smoother curve with fewer abrupt changes in slope. It is also more flexible and can pick up on more complex patterns and fluctuations in the data.

The longitudinal balanced data profile was compiled into subgroup

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Publication Date
Mon Aug 01 2022
Journal Name
Baghdad Science Journal
Perceptually Important Points-Based Data Aggregation Method for Wireless Sensor Networks
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The transmitting and receiving of data consume the most resources in Wireless Sensor Networks (WSNs). The energy supplied by the battery is the most important resource impacting WSN's lifespan in the sensor node. Therefore, because sensor nodes run from their limited battery, energy-saving is necessary. Data aggregation can be defined as a procedure applied for the elimination of redundant transmissions, and it provides fused information to the base stations, which in turn improves the energy effectiveness and increases the lifespan of energy-constrained WSNs. In this paper, a Perceptually Important Points Based Data Aggregation (PIP-DA) method for Wireless Sensor Networks is suggested to reduce redundant data before sending them to the

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Publication Date
Tue Jan 30 2024
Journal Name
International Journal Of Engineering Pedagogy (ijep)
The Impact of Two Proposed Strategies Based on Active Learning on Students' Achievement at the Computer and Their Social Intelligence
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Active learning is a teaching method that involves students actively participating in activities, exercises, and projects within a rich and diverse educational environment. The teacher plays a role in encouraging students to take responsibility for their own education under their scientific and pedagogical supervision and motivates them to achieve ambitious educational goals that focus on developing an integrated personality for today’s students and tomorrow’s leaders. It is important to understand the impact of two proposed strategies based on active learning on the academic performance of first-class intermediate students in computer subjects and their social intelligence. The research sample was intentionally selected, consis

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Publication Date
Mon Mar 25 2019
Journal Name
Al-academy
Educational -Learning Design in the Achievement and Motivation of Students in the High School towards Art Education: كنعان غضبان حبيب
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  The present study aimed at ((building an educational -learning design based on the theory of Merrill in (CDT) and measuring the effectiveness of this design in the motivation and achievement of the high school fifth grade students to art education in the subject of the history of modern art)). The research community is made of fifth grade preparatory students in the secondary school of Umm Ayman in the Directorate of Education of Baghdad / Ar-Rusafa in a simple random way. The study sample (58 students) was chosen from section (e) to study according to Merrill theory (CDT) and section (d) to study according to the traditional way.
The pilot design of the control and experimental equivalent groups that have partial control in t

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Publication Date
Thu Apr 04 2024
Journal Name
The International Tinnitus Journal
Efficacy of Sars-Cov-2 Vaccines on Severity of Coronavirus Disease in Iraq.
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Vaccination against novel Coronavirus (SARS-CoV-2) become highly recommended. In Iraq, three vaccines are available. They are Pfizer-Biontech, Oxford-AstraZenica, and Sino harm vaccines. A cross-sectional retrospective study was performed to a total of 2399 individual who are vaccinated with one of the available vaccines. People who are infected with Covid-19 before and/or after vaccination of either studied SARS-CoV-2 vaccines were also involved in this study (1175 case). Signs and symptoms have been reported for each of confirmed positive cases of Coronavirus disease. Statistical data analyses were applied to reveal the effect of different SARS-CoV-2 vaccines on the incidence of novel coronavirus disease among Iraqi population. Also, the

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Publication Date
Thu Jan 30 2020
Journal Name
Al-kindy College Medical Journal
Role of Multi-Detector CT Angiography in Assesmente of Athrosclerotic Coronary Artery Disease
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Background:  Imaging has a critical role in the diagnosis and evaluation of cardiac diseases, beginning with chest radiography and fluoro-scopy and progressing to coronary angio-graphy, echocardiography, nuclear medicine and recently  multidetector computed tomo-graphy (MDCT) as well as magnetic resonance (MR) imaging

Objective: To highlight the role of Multi-detector CT in the evaluation of coronary artery disease and its importance of being noninvasive diagnostic technique.

Methods: A cross sectional study for 20 patients. Patients were asked to fast 6 hours prior to the examination and the patients with heart rates above 65 beats per minute were given cardio-

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Publication Date
Tue Mar 31 2015
Journal Name
Al-khwarizmi Engineering Journal
Characterization of Biochar Produced from IRAQI Palm Fronds by Thermal Pyrolysis
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Abstract

The present paper focuses in a particular on the study of the biochar production conditions by the thermal pyrolysis of biomass from local Iraqi palm fronds, in the absence of oxygen. The biochar product can be used as soil improvers. The effect of temperature on the extent of the thermal pyrolysis process was studied in the range from 523 to 773K with a residence time of 15 minutes and nitrogen gas flow rate of 0.1 l/min. The produced biochar was characterized as will as biomass and degradation products. The results showed that the rate of biochar production decreases with the increasing in temperature, also it was noted that the normalized biochar surface area and pore size increases with the increasin

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Publication Date
Sun Mar 01 2015
Journal Name
Baghdad Science Journal
The Effect of Age and Gender on Fetuin-A and Some Biochemical parameters in Blood Sera of Iraqi patients with T2DM: A comparative study
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The serum protein test includes measurement of the level of total protein(albumin, globulin). Fetuin-A is a blood protein made in liver. It can inhibit insulin receptor, enhance insulin sensitivity and make the individuals more likely to develop type 2 diabetes, then disorder in lipid profile (Total cholesterol(TC), low density lipoprotein cholesterol (LDL-c), high density lipoprotein cholesterol (HDL-c), Triglyceride(TG) and very low density lipoprotein cholesterol (VLDL-c) . To evaluate Fetuin-A, total protein, albumin, globulin, HbAlc and lipid profile in 200 adult and elderly Iraqi patients with type 2 Diabetes Mellitus were taken and compare them with 200 subjects as a healthy control. The laboratory analysis(for patients and

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Publication Date
Wed May 17 2023
Journal Name
International Journal Of Computational Intelligence Systems
Prediction of ROP Zones Using Deep Learning Algorithms and Voting Classifier Technique
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Abstract<p>Retinopathy of prematurity (ROP) can cause blindness in premature neonates. It is diagnosed when new blood vessels form abnormally in the retina. However, people at high risk of ROP might benefit significantly from early detection and treatment. Therefore, early diagnosis of ROP is vital in averting visual impairment. However, due to a lack of medical experience in detecting this condition, many people refuse treatment; this is especially troublesome given the rising cases of ROP. To deal with this problem, we trained three transfer learning models (VGG-19, ResNet-50, and EfficientNetB5) and a convolutional neural network (CNN) to identify the zones of ROP in preterm newborns. The dataset to train th</p> ... Show More
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