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Exploring the Challenges of Diagnosing Thyroid Disease with Imbalanced Data and Machine Learning: A Systematic Literature Review

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
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
Oil spill classification based on satellite image using deep learning techniques

 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

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
Sun Apr 01 2018
Journal Name
Journal Of The Faculty Of Medicine Baghdad
The incidence and risk factors of hypocalcaemia after thyroid surgery

Background: Hypocalcaemia is a well-recognized complication of thyroid surgery. It is the most often transient event that occurs after extensive thyroid resection that may require calcium and/or vitamin D supplements to alleviate or prevent the symptoms.
Objective: of this study is to determine the incidence of hypocalcaemia after thyroid surgery and find out the risk factors involved regarding the patient age, gender, and muscular build, clinical diagnosis, the extent of surgery, ligation of the inferior thyroid artery, pathology report and the experience of the surgeon.
Patients and methods: This prospective study was carried out on 100 patients who underwent thyroid surgery for

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Publication Date
Mon Jan 02 2012
Journal Name
Journal Of The Faculty Of Medicine Baghdad
Clinical Implications In Pyle`s Disease, (Familial Metapyseal Dysplasia), Report Of Five Cases with Review Of The Literature.

Background: Pyle`s disease is a distinct skeletal dysplasia with defective metaphyseal modeling and Erlenmeyer-flask deformity of tubular bones.
Objectives: Clinical implications in five reported cases with mechanical bone properties different from normal bones were presented. One patient with Genu-valgum deformity had corrective osteotomy done with internal fixation showing osteotomy healing and sustained deformity correction with more than twelve years of follow up. Two patients presented with fractures and angular malalignment with abundant callus .The other two had insufficiency fractures due to repetitive low energy activities.
Results: Patients with Pyle`s disease have less than normal mechanical bone

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Publication Date
Sat Apr 01 2023
Journal Name
Baghdad Science Journal
Physiological and Hormonal Effects of Titanium Dioxide Nanoparticles on Thyroid Function and the Impact on Bodyweight in Male Rats

Fifty-four Sprague-Dawley albino adult male rats were classified into three main groups each of 18 rats treated for a particular duration (1,2, and 4) weeks respectively. Each group was subdivided into three subgroups each of six rats treated as follows; group (1) serve as normal control, group (2, and 3) intra-peritoneal treated with TiO2NPs (50,200) mg/kg respectively, body *weight of all rats was measured before and after the experiment, then rats were dissected at the end of each experiment and the weights of the thyroid was measured. The result showed a highly significant decrease (p<0.01) in thyroid gland weight, a highly significant increase (p<0.01) in body weights and TSH, while a highly significant decrease (p&

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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

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

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
Tue Mar 30 2021
Journal Name
Baghdad Science Journal
Hypothyroidism and AMH in Iraqi Patients with Chronic Kidney Disease

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
Sun Oct 02 2016
Journal Name
Journal Of The Faculty Of Medicine Baghdad
The predictive value of selected ultrasound features in evaluating malignancy in thyroid nodules

Background: Thyroid ultrasound has been widely used to differentiate benign from malignant nodules; many investigators have tried to point out few ultrasonographic features in order to identify those lesions, which are at a higher risk of malignancy.
Objectives: To evaluate the efficacy of selected conventional ultrasound (US) features of thyroid focal lesions useful for predicting malignancy and establishing indications for fine-needle aspiration cytology (FNAC).
Patients and Methods:Two hundred and four consecutive patients with thyroid nodules who visited the outpatient clinic of the surgical department of Tikrit University teaching hospital for the period from January 2011 to April 2014, and who underwent surgery for clinical s

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Publication Date
Wed Aug 30 2023
Journal Name
Iraqi Journal Of Science
Review of Smishing Detection Via Machine Learning

     Smishing is a cybercriminal attack targeting mobile Short Message Service (SMS) devices that contains a malicious link, phone number, or email. The attacker intends to use this message to steal the victim's sensitive information, such as passwords, bank account details, and credit cards. One method of combating smishing is to raise awareness and educate users about the various tactics used by SMS phishers. But even so, this method has been criticized for becoming inefficient because smishing tactics are continually evolving. A more promising anti-smishing method is to use machine learning. This paper introduces a number of machine learning algorithms that can be used for detecting smishing. Furthermore, the differences and simil

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