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 research aims at the possibility of measuring the technical and scale efficiency (SE) of the departments of the College of Administration and Economics at the University of Baghdad for a period lasting 8 years, from the academic year 2013-2014 to 2018-2019 using the method of Applied Data Analysis with an input and output orientation to maintain the distinguished competitive position and try to identify weaknesses in performance and address them. Nevertheless, the research problem lies in diagnosing the most acceptable specializations in the labor market and determining the reasons for students’ reluctance to enter some departments. Furthermore, the (Win4DEAp) program was used to measure technical and scale efficiency (SE) and rely on
... Show MoreHot-wire cutting is one of the important, non-traditional thermomechanical way to cut polymer, usually expanded foam and extruded foam, in low volume manufacturing. The study and analysis of Hot-Wire cutting parameters play an important role to enhance the quality and accuracy of the process and products. The effects on the surface have been investigated by using experimental tests designed according to the Taguchi orthogonal array (OA). In this study, four parameters with five levels for each parameter have been used: [temperature of wire (A) (100, 120, 130, 150, 160) °C], [diameter of wire (B) (0.3,0.4,0.5,0.7,0.8) mm], [velocity of cutting (C) (200, 300,400,500,600) mm/min], [and density of foam (D) (0.01,0.0
... Show MoreMultiple sclerosis (MS) is a chronic, inflammatory, immune mediated disease of the central nervous system, mostly affecting young adults with mean age of 30 years, twice as high in women compared to men. The etiology of MS is not fully elucidated. MS symptoms are directly related to demyelination and axonal loss, along with other psychological symptoms, can result in functional limitations, disability and reduced quality of life (QoL). The QoL assessments in patients with a chronic disease may contribute to improving treatment and could even be of prognostic value. The goals of this study were to compare the QoL of Iraqi patients with relapsing remitting multiple sclerosis (RRMS),using three different diseas
... Show MoreA gantry robot is one of the most common types of industrial robots with linear movement. This type of robot is also known as a Cartesian or linear robot. It is an automated industrial system that moves along linear paths, enabling it to create a 3D envelope of the space in which it operates. A robot of this type has a standardised configuration process because it can have several sets of axes, such as X, Y and Z. The gantry robot picks up products from several places, so it can search through various locations. Afterwards, it carefully deposits the products on a conveyor belt for the next stage of the procedure or final shipment. This integration enables continuous and automated material flow
... Show MoreThe provision of safe water for people is a human right; historically, a major number of people depend on groundwater as a source of water for their needs, such as agricultural, industrial or human activities. Water resources have recently been affected by organic and/or inorganic contaminants as a result of population growth and increased anthropogenic activity, soil leaching and pollution. Water resource remediation has become a serious environmental concern, since it has a direct impact on many aspects of people’s lives. For decades, the pump-and-treat method has been considered the predominant treatment process for the remediation of contaminated groundwater with organic and inorganic contaminants. On the other side, this tech
... Show MoreThe tourism industry has undergone exponential transformation, reshaped by online travel agencies (OTAs), shifting consumer preferences, and technological advancements. Established OTAs like TripAdvisor and Travelocity face pressures to adapt their strategies to capitalize on these disruptive landscape changes. This research involves a comparative analysis examining the key challenges confronting TripAdvisor and Travelocity, with a focus on opportunities to leverage artificial intelligence (AI) in enhancing personalization and the traveler experience. The study utilizes publicly available data on the companies and academic literature on AI innovation diffusion. Findings reveal that while TripAdvisor has actively developed AI-based trip plan
... Show MoreThe status of the semi total stoppage and non-use and waste of economic made studying and analyzing Dutch disease of high importance because it is a major cause in aggravation of this status which happened to the Iraqi economy in almost complete way and the relative big importance that oil source has and its domination on the largest percentage in the gross domestic product and exports that Iraqi economy is relying largely in funding the national budget made the concentration of the study on this subject an important and necessary within the important economic events that Iraqi economy witnessed after 2003 till 2016 to give a clear and an overall picture of the reality of the unilateral Iraqi economy under the status of semi tota
... Show MoreThis research has come out with that, function-based responsibility accounting system has harmful side – effects preventing it of achieving its controlling objective, that is, goal congruence, which are due to its un integrated measures, its focus on measuring measurable behaviors while neglecting behaviors that are hardly measured, and its dependence on standard operating procedures.
In addition, the system hypotheses and measures are designed to fit previous business environment, not the current environment.
The research has also concluded that the suggestive model, that is, activity-based responsibility accounting is designed to get ride of harmful side – effects of functi
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