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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
Sat Dec 07 2019
Journal Name
Journal Of The Faculty Of Medicine Baghdad
Incidental Thyroid Carcinoma in Patients Treated Surgically for Thyroid Disease

Background: The occurrence of incidental thyroid cancer (ITC) has increased by three times during the last decades and this rise could be attributed to many factors. To limit the prevalence of ITC with goiter especially nodular goiter, total thyroidectomy can become a procedure of choice.

Objective: To determine the extent of incidental thyroid carcinoma (ITC) and to plan a proper preoperative diagnostic work up and a convenient operative procedure for patients with different thyroid diseases.


Results:
ITC was found in 77 patients (19.15%). While, 63 patients with non-toxic MNG (15.6%), 12 patients with non-toxic solitary thyroid nodule (3%) and two patients (0.5%) wi

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Publication Date
Sun Nov 08 2020
Journal Name
Journal Of The Faculty Of Medicine Baghdad
the The Role of Ultrasound in the Diagnosis of Malignant Thyroid Nodules

Background: Thyroid nodules are very common in clinical practice. Although most of thyroid nodules are benign, it is crucial to checkout which nodules are more likely to be malignant. Ultrasound is a major diagnostic tool for screening and evaluating thyroid diseases because it is safe, non-invasive, non-radioactive and effective.
Objective: The aim is to identify the role of ultrasound in assessing thyroid nodules and to review various ultrasound criteria predicting malignancy.
Patients and methods: A case series study conducted during the period from January 2015 to February 2016 at the First Surgical Unit, Department of Surgery, Baghdad Teaching Hospital by a team of surgeons. One hundred eighty Patients who underwent surgical i

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Publication Date
Mon Dec 05 2022
Journal Name
Baghdad Science Journal
IPv6 Security Issues: A Systematic Review Following PRISMA Guidelines

Since Internet Protocol version 6 is a new technology, insecure network configurations are inevitable. The researchers contributed a lot to spreading knowledge about IPv6 vulnerabilities and how to address them over the past two decades. In this study, a systematic literature review is conducted to analyze research progress in IPv6 security field following the Preferred Reporting Items for the Systematics Review and Meta-Analysis (PRISMA) method. A total of 427 studies have been reviewed from two databases, IEEE and Scopus. To fulfil the review goal, several key data elements were extracted from each study and two kinds of analysis were administered: descriptive analysis and literature classification. The results show positive signs of t

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Publication Date
Sun Oct 02 2016
Journal Name
Journal Of The Faculty Of Medicine Baghdad
Incidental thyroid carcinoma

Background: thyroid carcinoma is the most common endocrine carcinoma as it accounts for almost 90% of all endocrine malignancies. The term incidental denoted malignant tumors of the thyroid gland detected by post-operative biopsy results of the resected specimens resected from benign thyroid diseases. Among the incidental thyroid malignancies, papillary carcinoma is the commonest pathological type.
Objectives : To determine the incidence of incidental thyroid carcinoma and to insist on accurate preoperative diagnostic work up of patients with thyroid diseases.
Patients & Methods: A prospective study, which was conducted during the period from March 2013 to April 2014 at Baghdad teaching hospital first surgical unit by the same

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Publication Date
Tue Dec 05 2023
Journal Name
Baghdad Science Journal
Processing of Polymers Stress Relaxation Curves Using Machine Learning Methods

Currently, one of the topical areas of application of machine learning methods is the prediction of material characteristics. The aim of this work is to develop machine learning models for determining the rheological properties of polymers from experimental stress relaxation curves. The paper presents an overview of the main directions of metaheuristic approaches (local search, evolutionary algorithms) to solving combinatorial optimization problems. Metaheuristic algorithms for solving some important combinatorial optimization problems are described, with special emphasis on the construction of decision trees. A comparative analysis of algorithms for solving the regression problem in CatBoost Regressor has been carried out. The object of

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Publication Date
Sun Oct 01 2017
Journal Name
Journal Of The Faculty Of Medicine Baghdad
Pre-operative serum TSH level estimation for predicting malignant nodular thyroid disease

Background: the aim of this study was to assess the value of serum thyroid–stimulating hormone (TSH) levels in predicting malignancy in patients with nodular thyroid disease (NTD). Objective: The aim was to examine the relationship between preoperative TSH and differentiated thyroid cancer (DTC).
Patients and Method: all patients with NTD who were admitted in the first surgical unit of Baghdad teaching hospital and assessed for preoperative TSH level before subjecting them for thyroidectomy from first of April 2014 to 31 of January 2016, were included in the study. A preoperative database sheets including Age, gender, nodule size, and pathology were evaluated. Logistic regression analysis was used t

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Publication Date
Wed Mar 10 2021
Journal Name
Baghdad Science Journal
Detecting Textual Propaganda Using Machine Learning Techniques

Social Networking has dominated the whole world by providing a platform of information dissemination. Usually people share information without knowing its truthfulness. Nowadays Social Networks are used for gaining influence in many fields like in elections, advertisements etc. It is not surprising that social media has become a weapon for manipulating sentiments by spreading disinformation.  Propaganda is one of the systematic and deliberate attempts used for influencing people for the political, religious gains. In this research paper, efforts were made to classify Propagandist text from Non-Propagandist text using supervised machine learning algorithms. Data was collected from the news sources from July 2018-August 2018. After annota

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Publication Date
Tue Dec 05 2023
Journal Name
Baghdad Science Journal
AlexNet-Based Feature Extraction for Cassava Classification: A Machine Learning Approach

Cassava, a significant crop in Africa, Asia, and South America, is a staple food for millions. However, classifying cassava species using conventional color, texture, and shape features is inefficient, as cassava leaves exhibit similarities across different types, including toxic and non-toxic varieties. This research aims to overcome the limitations of traditional classification methods by employing deep learning techniques with pre-trained AlexNet as the feature extractor to accurately classify four types of cassava: Gajah, Manggu, Kapok, and Beracun. The dataset was collected from local farms in Lamongan Indonesia. To collect images with agricultural research experts, the dataset consists of 1,400 images, and each type of cassava has

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Publication Date
Sun Sep 02 2018
Journal Name
Journal Of The Faculty Of Medicine Baghdad
Immunohistochemistry on cell blocks a method for pre-operative diagnosis of papillary thyroid carcinoma by FNAC

Background: Papillary thyroid carcinoma (PTC) is the commonest thyroid cancer. Cases in category-
5a of Bethesda system (suspicious for papillary carcinoma) are treated by surgical lobectomy followed
by total thyroidectomy if histopathology confirms papillary carcinoma. In order to reduce surgical
procedures to one this was conducted.
Objectives: evaluation of role of immunohistochemistry in pre-operative diagnosis of papillary thyroid
carcinoma on cell blocks.
Materials and Method: Cell blocks were taken from cases labelled category-5a for histopathology and
immunohistochemistry using three markers (CK-19, Thyro-peroxidase, and BRAFv600E mutation).
Results: were highly sensitive, and specific. The use of more tha

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Publication Date
Wed Apr 15 2020
Journal Name
Journal Of The Faculty Of Medicine Baghdad
collision tumor of thyroid gland a case report

collision tumor is the presence of two histopathologically distinct tumors in the same anatomical site.  It is a rare pathology of the thyroid gland that makes diagnosis and treatment challenging.  This is a case report of a collision tumor of the thyroid gland.

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