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
Fibroblast growth factors-23 (FGF-23) are a class of cell signaling proteins produced by macrophages. They have a range of roles, but they play a particularly important role in the development of animal cells, where they are essential for appropriate growth. Phosphate, which is found in the body as both organic and mineral phosphate, plays crucial roles in cell structure, communication, and metabolism. Most phosphate in the body resides in bone, teeth, and inside cells, with less than 1% circulating in serum. The aim of the study is to evaluate the levels of the Fibroblast Growth Factors-23 and phosphate and receiver operating characteristic (ROC) in acromegaly patients against healthy control. A case control study Fibroblast Growth Fact
... Show MoreWheat is rich in sources of fiber, oligosaccharides, and resistant starch, simple carbohydrates which may have a protective role against carcinoma. Additionally, Whole wheat/bran as well includes contains phytochemicals such as flavonoids, lignans, folate, phytosterols, phenolic acids, and tocols. The above phytochemicals suitable forms antioxidant and cholesterol-reducing activities. Phytoestrogens are regarded as especially essential in the preventative measures of hormonally dependent malignancies such as breast cancer (BC). In this study lowered BC risk has been associated with whole grain/bran consumption with an odds ratio (OR=0.24 and 95 %CI=0.10-0.56). Wheat/bran appears to have a reliable protective impact against BC. While intake
... Show MoreThe cheif aim of the present investigation is to develop Leslie Gower type three species food chain model with prey refuge. The intra-specific competition among the predators is considered in the proposed model. Besides the logistic growth rate for the prey species, Sokol Howell functional response for predation is chosen for our model formulation. The behaviour of the model system thoroughly analyses near the biologically significant equilibria. The linear stability analysis of the equilibria is carried out in order to examine the response of the system. The present model system experiences Hopf bifurcation depending on the choice of suitable model parameters. Extensive numerical simulation reveals the validity of the proposed model.
The study aims budget in grades use of smart phones to individuals (sample) according variable sex (males and females) and used researcher descriptive analytical method consisted sample of (300) students have chosen the way stratified random, and the study variables (academic achievement of students, sex and the use of Smart phones) resolution was adopted as a tool for data collection. The most important results of the study that females are more commonly used for smart phones, as well as the existence of a positive relationship between the inverse statistically significant use of smart phones and the rate of school for students and the use of smart phones h
... Show MoreBreast cancer is one of the most important malignant diseases all over the world. The incidence of breast cancer is increasing around the world and it is still the leading cause of cancer mortality An Approximately 1.3 million new cases were diagnosed worldwide last year. With areas rising increasing, risk factors for breast cancer including obesity, early menarche, alcohol and smoking, environmental contamination and reduced or late birth rates become more prevalent. In Iraq, breast cancer ranks first among types of cancers diagnosed in women. This study was conducted on one hundred twenty women with breast cancer that was evaluated and investigated for the possible role of the risk factors on the development of breast cancer in females. T
... Show MoreThe Influence of Some Vitamins and Biochemical Parameters on Iraqi Females’ Patients with Malignant Breast Cancer"