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
Most of the Internet of Things (IoT), cell phones, and Radio Frequency Identification (RFID) applications need high speed in the execution and processing of data. this is done by reducing, system energy consumption, latency, throughput, and processing time. Thus, it will affect against security of such devices and may be attacked by malicious programs. Lightweight cryptographic algorithms are one of the most ideal methods Securing these IoT applications. Cryptography obfuscates and removes the ability to capture all key information patterns ensures that all data transfers occur Safe, accurate, verified, legal and undeniable. Fortunately, various lightweight encryption algorithms could be used to increase defense against various at
... Show MoreDrought is a natural phenomenon in many arid, semi-arid, or wet regions. This showed that no region worldwide is excluded from the occurrence of drought. Extreme droughts were caused by global weather warming and climate change. Therefore, it is essential to review the studies conducted on drought to use the recommendations made by the researchers on drought. The drought was classified into meteorological, agricultural, hydrological, and economic-social. In addition, researchers described the severity of the drought by using various indices which required different input data. The indices used by various researchers were the Joint Deficit Index (JDI), Effective Drought Index (EDI), Streamflow Drought Index (SDI), Sta
... Show MoreBackground: Polycystic ovarian syndrome (PCOS) is the most endocrine disorder common effect (5-10) % in women at reproductive age. Thyroid dysfunction with PCOS is both representing parts of the endocrine system; this link leads to problems of ovulation and pregnancy. Aims: to investigate the prevalence of thyroid disorder in PCOS woman, and associate the outcome with obesity. Patient and method: This study was conducted in Al-batol Teaching Hospital in Baquba City /Iraq. The results reviewed included 63 women: 45 PCOS were diagnosed on the basis of Rotterdam criteria, 18 as control, aged 17- 44 year. The samples have been collected at second day of menstrual cycle, to test fT3, fT
... Show MoreForty – two elderly hypothyroidism patients and forty – two apparently healthy as control groups , divided to (21) male (M) and (21) female (F) also (21) control male C(M) and (21) control female C(F) aged > 60 years, were tested for the presence of thyroid peroxidase autoantibody (TPo – Ab) and thyroglobulin auto antibody (Tg – Ab) , also for Se and Zn levels in their sera . The results revealed a significant increase in (TPO – Ab) and (Tg – Ab) for group (M) and (F) compared to control group , also a siginificant increase in TPo – Ab and Tg – Ab for (F) compared to (M) was found. A significant decrease in Se and Zn level for (M) and (F) compared to control group, while no significant difference between (M) and (F). In conc
... Show MoreThe present study aimed to investigate the morphological description and histological structure of thyroid gland in Herpestes javanicus . The results revealed that thyroid gland in adult Herpestes javanicus is located in the neck region just below the larynx and attached to the trachea . Histological study revealed that thyroid gland in H. javanicus surrounded by a capsule of losse connective tissue and the thyroid gland mainly formed from follicles within different sizes. The results showed that the follicle consists of three compenets represented by follicular lining cells, basal parafollicular cells and the colloid. Microscopical examination revealed that the follicular lining tissue is either to be simpl
... Show MoreMixed-effects conditional logistic regression is evidently more effective in the study of qualitative differences in longitudinal pollution data as well as their implications on heterogeneous subgroups. This study seeks that conditional logistic regression is a robust evaluation method for environmental studies, thru the analysis of environment pollution as a function of oil production and environmental factors. Consequently, it has been established theoretically that the primary objective of model selection in this research is to identify the candidate model that is optimal for the conditional design. The candidate model should achieve generalizability, goodness-of-fit, parsimony and establish equilibrium between bias and variab
... Show MoreBackground: Chronic kidney disease is a condition that results from an indefinite change in the structure and function of the kidneys. A slow, steady progression characterizes it and is irreversible. Objectives: This study aims to evaluate the findings of certain biochemical and hematological tests in samples from Iraqi CKD patients. Methods: This study included 90 subjects, where 70 patients with chronic kidney disease and 20 healthy individuals. Blood samples were collected from the patients during their visits to Ghazi Al-Hariri Surgical Specialties' Hospital- Medical City, Baghdad, Iraq. Age, sex and body mass index were assessed for each participant followed by renal function tests [serum blood urea, creatinine, uric acid a
... Show MoreThe present study evaluated the anti- Helicobacter pylori IgG, IgA and the role of virulence factor of H. pylori Vacuolating associated cytotoxin gene (Vac A) as a risk factors for CAD. The levels of serum IgG and IgA was done by indirect immunofluorescent (IIF) whereas Vac A measured by enzyme linked immunosorbent assay (ELISA). Ibn Al-Bitar specialist center for cardiac surgery laboratory and Ministry of Health/ Baghdad/ Iraq, between May and October 2018. Seventy Iraqi patients with CAD were enrolled in this study, their ages ranged between 40-84 years ; and 20 individuals as a control group which was divided into 2 subgroups: 10 apparently healthy volunteers (negative control) and the other subgroup contained 10 with normal coronary art
... Show More