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
The purpose of this paper is to apply different transportation models in their minimum and maximum values by finding starting basic feasible solution and finding the optimal solution. The requirements of transportation models were presented with one of their applications in the case of minimizing the objective function, which was conducted by the researcher as real data, which took place one month in 2015, in one of the poultry farms for the production of eggs
... Show MoreThe support vector machine, also known as SVM, is a type of supervised learning model that can be used for classification or regression depending on the datasets. SVM is used to classify data points by determining the best hyperplane between two or more groups. Working with enormous datasets, on the other hand, might result in a variety of issues, including inefficient accuracy and time-consuming. SVM was updated in this research by applying some non-linear kernel transformations, which are: linear, polynomial, radial basis, and multi-layer kernels. The non-linear SVM classification model was illustrated and summarized in an algorithm using kernel tricks. The proposed method was examined using three simulation datasets with different sample
... Show MoreWater represents as a basic intellectual material in the myths of creation and the start of formation, Thus, water has turned into an intellectual material in literary mythological texts in addition to its function in sculptural Mesopotamian sculpture. The research is in three sections: the first section deals with Myth, its concept, peculiarities and types, the second section is about mythological literature, the third section is about the idea of water and mythical literature. The question research question here is that does the idea of water have any impact on mythological literature? And Does it link to sculptural products? The importance of the research is that it shows the human imagination and its relationship to functioni
... Show MoreResearch included the preparation of medicinal substances ( propyl thiouracil). Which is the rule thiourea and related compounds a fundamental rule in preparation fall within the range of drugs of anti-thyroid activity (Antithyroid Drug ) , this drug prevents the thyroid hormone production against excessive activity of the thyroid gland .That the formation of iodine is important for their impact on hormone secretion thyroid , the two types, thyroxin or T4 is the main hormone ,Triiodothyronine or T3, and these hormones released by hormone regulator called (TSH) . Article attend thiourea treatment with an alcohol- soluble sodium and added to the interaction rule b- oxo ester after adjusting the PH=4 output ( propylthiouracil ) the
... Show MoreStudy was done in the period between (2015–2017) in biology department in college of Education for pure science/Ibn Al-Haitham at Baghdad University and in Pathology department/college of medicine at Al-Nahrain University. The study was retrospectively designed. The clinicopathological parameters were obtained from patients’ admission case sheets and pathology reports (age, gender). The presents study included 120 patients having thyroid nodules, classified according to results of histopathology into 4 groups, 30 patients within each; the first group included patients with follicular adenoma, the second group included patients with follicular carcinoma, the third group included patients with follicular variant of papillary carcinoma (FV
... Show MoreAge and BMI may be used to diagnosis of thyroid autoimmune disease. One hundred Iraqi women with age ranged from 18 to 60 years participate in this research, 50 of them were hypothyroidism patients, 30 were hyperthyroidism patients and the other 20 were euthyroidism served as controls. Blood samples were collected from the studied subjects to determine thyroid profile [free triiodothyronine (FT3), free tetraiodothyronine (FT4) and thyroid stimulating hormone (TSH)], thyroid antibodies [anti-thyroid peroxidase (anti-TPO), anti-thyroglobulin (anti-Tg), and anti-thyroid stimulating hormone receptor (anti-TSHR)], and levels of vitamin D (vit D), calcium (Ca), and phosphorus (P) using different analysis techniques. When the effect of age
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