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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 Mar 30 2021
Journal Name
Baghdad Science Journal
Hypothyroidism and AMH in Iraqi Patients with Chronic Kidney Disease
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This study was conducted to investigate thyroid function and Anti-Müllerian hormone (AMH) in (Chronic kidney disease) CKD patients by evaluating their levels in CKD patients, 50 patients were diagnosed to have CKD stage-5, their ages ranged between 20-50 years (25 males and 25 females) who attended the Nephrology and Transplant Center in Medical City of Baghdad- Iraq, they were recruited from April 2018 to July 2018 and were enrolled into the study. The control group consisted of 20 healthy individuals, their ages ranged between 20-48 years (10 males and 10 females). The study showed non-significant (p>0.05) increase in AMH level in CKD patients compared to the control group. On the other hand, TSH was recorded a highly significant (

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Publication Date
Thu Feb 01 2024
Journal Name
Bulletin Of Electrical Engineering And Informatics
A systematic literature review for smart hydroponic system
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Hydroponics is the cultivation of plants by utilizing water without using soil which emphasizes the fulfillment of the nutritional needs of plants. This research has introduced smart hydroponic system that enables regular monitoring of every aspect to maintain the pH values, water, temperature, and soil. Nevertheless, there is a lack of knowledge that can systematically represent the current research. The proposed study suggests a systematic literature review of smart hydroponics system to overcome this limitation. This systematic literature review will assist practitioners draw on existing literature and propose new solutions based on available knowledge in the smart hydroponic system. The outcomes of this paper can assist future r

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Publication Date
Tue Aug 15 2023
Journal Name
Journal Of Economics And Administrative Sciences
Machine Learning Techniques for Analyzing Survival Data of Breast Cancer Patients in Baghdad
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The Machine learning methods, which are one of the most important branches of promising artificial intelligence, have great importance in all sciences such as engineering, medical, and also recently involved widely in statistical sciences and its various branches, including analysis of survival, as it can be considered a new branch used to estimate the survival and was parallel with parametric, nonparametric and semi-parametric methods that are widely used to estimate survival in statistical research. In this paper, the estimate of survival based on medical images of patients with breast cancer who receive their treatment in Iraqi hospitals was discussed. Three algorithms for feature extraction were explained: The first principal compone

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Publication Date
Thu Jan 30 2020
Journal Name
Al-kindy College Medical Journal
Thyroid Hemiagenesis with Ipsilateral Parathyroid Adenoma; Case report with Review of the Literature
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Thyroid hemiagenesis (THA) is a rare congenital anomaly in which one lobe of thyroid gland fails to develop during embryological stage. Agenesis may be unilateral, total or isthmic. Left thyroid lobe is more commonly involved than right lobe in hemiagenesis. Agenesis of the isthmus was seen in 50% of cases. Left sided hemiagenesis is more common than right sided hemiagenesis with a Left to right ratio of 4:1. Clinically patients can be euthyroid, hypothyroid or hyperthyroid. Often it is diagnosed as an incidental finding during ultrasonography (USG) study of neck, which can easily diagnose this condition.

Actual incidence of THA is unknown; most cases are diagnosed in patients admitted for thyroid scan or thyroid surgery because

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Publication Date
Wed Dec 01 2021
Journal Name
Baghdad Science Journal
Association of Circulating MicroRNA-142-3p with Graves Disease
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This study aims to investigate the possible role of circulating microRNA-142-3p (miR-142-3p) in the
development of graves disease (GD) and its association with the antibody directed against thyroid
stimulating hormone receptor (TSHR-Ab) production in patients with GD. Forty patients with positive
TSHR-Ab enrolled in this study were divided ,based on treatment, into (22 untreated (newly diagnosed) and
18 treated patients) and based on family history (30 with positive family history and 10 with negative family
history). In addition to forty healthy subjects with sex and age matching as a control group. The expression
level of circulating miR-142-3p was determined by two steps reverse transcription polymerase c

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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
Oil spill classification based on satellite image using deep learning techniques
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 An oil spill is a leakage of pipelines, vessels, oil rigs, or tankers that leads to the release of petroleum products into the marine environment or on land that happened naturally or due to human action, which resulted in severe damages and financial loss. Satellite imagery is one of the powerful tools currently utilized for capturing and getting vital information from the Earth's surface. But the complexity and the vast amount of data make it challenging and time-consuming for humans to process. However, with the advancement of deep learning techniques, the processes are now computerized for finding vital information using real-time satellite images. This paper applied three deep-learning algorithms for satellite image classification

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Publication Date
Sun Jun 20 2021
Journal Name
Baghdad Science Journal
A Comprehensive Review on Medical Image Steganography Based on LSB Technique and Potential Challenges
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The rapid development of telemedicine services and the requirements for exchanging medical information between physicians, consultants, and health institutions have made the protection of patients’ information an important priority for any future e-health system. The protection of medical information, including the cover (i.e. medical image), has a specificity that slightly differs from the requirements for protecting other information. It is necessary to preserve the cover greatly due to its importance on the reception side as medical staff use this information to provide a diagnosis to save a patient's life. If the cover is tampered with, this leads to failure in achieving the goal of telemedicine. Therefore, this work provides an in

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Publication Date
Sat Oct 20 2018
Journal Name
Journal Of Economics And Administrative Sciences
THE IMPACT OF MANAGEMENT CONTROL SYSTEMS (MCS) ON ORGANIZATIONS PERFORMANCE A LITERATURE REVIEW
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The impact of management control systems (MCS) on organizations performance empirical research has been the subject of numerous studies during the past decade in developed and emerging economies. In the contemporary competitive, complex and changing global business environment, firms are being challenged to adopt business models that enable them to address the strategic uncertainties and risks they face in their business environments. The main issue of this study is that management accounting researchers argue that one of the ways firms can continually rejuvenate themselves to survive and succeed in these complex and uncertain environments is to understand the role of management control systems in Formulating a b

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Publication Date
Tue Dec 01 2020
Journal Name
Baghdad Science Journal
Detection of Suicidal Ideation on Twitter using Machine Learning & Ensemble Approaches
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Suicidal ideation is one of the most severe mental health issues faced by people all over the world. There are various risk factors involved that can lead to suicide. The most common & critical risk factors among them are depression, anxiety, social isolation and hopelessness. Early detection of these risk factors can help in preventing or reducing the number of suicides. Online social networking platforms like Twitter, Redditt and Facebook are becoming a new way for the people to express themselves freely without worrying about social stigma. This paper presents a methodology and experimentation using social media as a tool to analyse the suicidal ideation in a better way, thus helping in preventing the chances of being the victim o

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Publication Date
Sun Dec 10 2023
Journal Name
Journal Of Applied Engineering And Technological Science (jaets)
The Role of Artificial Intelligence in Diagnosing Heart Disease in Humans: A Review
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The electrical activity of the heart and the electrocardiogram (ECG) signal are fundamentally related. In the study that has been published, the ECG signal has been examined and used for a number of applications. The monitoring of heart rate and the analysis of heart rhythm patterns, the detection and diagnosis of cardiac diseases, the identification of emotional states, and the use of biometric identification methods are a few examples of applications in the field. Several various phases may be involved in the analysis of electrocardiogram (ECG) data, depending on the type of study being done. Preprocessing, feature extraction, feature selection, feature modification, and classification are frequently included in these stages. Ever

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