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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 Jan 01 2019
Journal Name
Indian Journal Of Public Health Research & Development
Active Ocular involvement in iraqi Patients with Behçet's Disease
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Publication Date
Thu Jun 30 2022
Journal Name
Journal Of Economics And Administrative Sciences
The Use of the Regression Tree and the Support Vector Machine in the Classification of the Iraqi Stock Exchange for the Period 2019-2020
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 The financial markets are one of the sectors whose data is characterized by continuous movement in most of the times and it is constantly changing, so it is difficult to predict its trends , and this leads to the need of methods , means and techniques for making decisions, and that pushes investors and analysts in the financial markets to use various and different methods in order to reach at predicting the movement of the direction of the financial markets. In order to reach the goal of making decisions in different investments, where the algorithm of the support vector machine and the CART regression tree algorithm are used to classify the stock data in order to determine

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Publication Date
Mon Jun 01 2015
Journal Name
Journal Of Economics And Administrative Sciences
Diagnosis of medical errors and the responsibility of nursing staff reported in Sadr Teaching Hospital
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The study aims to determine the responsibility of nursing staff for medical errors that accompany the surgery at the hospital , which is one of the important issues that the importance of determining the responsibility of landlords nursing medical errors in the hospital was the rationale in choosing the subject. Since study included cases of errors nursing staff of (22) case. While the checklist distributed to a sample of nursing Angel Group in Sadr Teaching Hospital 's (100) nurs According to the problem, the study in determining the responsibility of nursing staff for medical errors that are not important for the hospitals. Has shown results of the study agreement members of the study sample that the clarity of the power posses

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Publication Date
Sun Jun 01 2008
Journal Name
Journal Of Economics And Administrative Sciences
تحليل – الكلفة – الحجم – الربح – في ظل نظام الكلفة على أساس الأنشطة
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Recent advancement in production technologist of manufacturing processes have left an important effects upon cost structure. Moreover the problem for providing necessary and adequate information for managerial decision making.

Therefore the cost – volume – profit analysis under the new activity based costing has replace the old method for Analysing the relation between C.V.P with respect to profit planning and control.

In brief the C.V.P object is to discuss the effect of changes on profit resulting from changes in sales volume, cost of manufacturing and selling price.

This study consists of four chapters:

The first chapter dea

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Publication Date
Sat Sep 01 2007
Journal Name
Journal Of Economics And Administrative Sciences
أثر تحليل كلف النوعية على أساس الانشطة في تحقيق الميزة التنافسية
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يتطلب تحقيق تمايز الوحدة الاقتصادية في ظل استعمال تقنيات الأعمال الحديثة وازدياد المنافسة وعالمية الأعمال ضرورة الاهتمام بمستوى نوعية المنتجات وما تتطلبه هذه النوعية من كلف والتي تسمى بكلف النوعية، إذ ان العديد من الشركات العالمية قد قامت بدراسة وتحليل هذه الكلف ووضع برامج خاصة بها بهدف تخفيضها إلى أدنى حدٍ ممكن وبما يكفل تحقيق العديد من المنافع والتوفيرات في هذه الكلف وبما يرشد عملية اتخاذ القرارات

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Publication Date
Sat Apr 01 2023
Journal Name
Baghdad Science Journal
Interior Visual Intruders Detection Module Based on Multi-Connect Architecture MCA Associative Memory
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Most recent studies have focused on using modern intelligent techniques spatially, such as those
developed in the Intruder Detection Module (IDS). Such techniques have been built based on modern
artificial intelligence-based modules. Those modules act like a human brain. Thus, they should have had the
ability to learn and recognize what they had learned. The importance of developing such systems came after
the requests of customers and establishments to preserve their properties and avoid intruders’ damage. This
would be provided by an intelligent module that ensures the correct alarm. Thus, an interior visual intruder
detection module depending on Multi-Connect Architecture Associative Memory (MCA)

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Publication Date
Wed Aug 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
Comparison Some Estimation Methods Of GM(1,1) Model With Missing Data and Practical Application
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This paper presents a grey model GM(1,1) of the first rank and a variable one and is the basis of the grey system theory , This research dealt  properties of grey model and a set of methods to estimate parameters of the grey model GM(1,1)  is the least square Method (LS) , weighted least square method (WLS), total least square method (TLS) and gradient descent method  (DS). These methods were compared based on two types of standards: Mean square error (MSE), mean absolute percentage error (MAPE), and after comparison using simulation the best method was applied to real data represented by the rate of consumption of the two types of oils a Heavy fuel (HFO) and diesel fuel (D.O) and has been applied several tests to

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Publication Date
Mon Jul 18 2022
Journal Name
World Bulletin Of Public Health (wbph)
WASTEWATER TREATMENTS: A REVIEW
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Many water supplies are now contaminated by anthropogenic sources such as domestic and agricultural waste, as well as manufacturing activities, the public's concern about the environmental effects of wastewater contamination has grown. Several traditional wastewater treatment methods, such as chemical coagulation, adsorption, and activated sludge, have been used to eliminate pollution; however, there are several drawbacks, most notably high operating costs, because of its low operating and repair costs, the usage of aerobic waste water treatment as a reductive medium is gaining popularity. Furthermore, it is simple to produce and has a high efficacy and potential to degrade pollu

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Publication Date
Thu Dec 01 2022
Journal Name
Scientific Research Journal Of Engineering And Computer Science
Cryptography Techniques - A Review
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Publication Date
Mon Mar 31 2025
Journal Name
International Journal Of Advanced Technology And Engineering Exploration
Breast cancer survival rate prediction using multimodal deep learning with multigenetic features
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Breast cancer is a heterogeneous disease characterized by molecular complexity. This research utilized three genetic expression profiles—gene expression, deoxyribonucleic acid (DNA) methylation, and micro ribonucleic acid (miRNA) expression—to deepen the understanding of breast cancer biology and contribute to the development of a reliable survival rate prediction model. During the preprocessing phase, principal component analysis (PCA) was applied to reduce the dimensionality of each dataset before computing consensus features across the three omics datasets. By integrating these datasets with the consensus features, the model's ability to uncover deep connections within the data was significantly improved. The proposed multimodal deep

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