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
Currently, there is an intensive development of bipedal walking robots. The most known solutions are based on the use of the principles of human gait created in nature during evolution. Modernbipedal robots are also based on the locomotion manners of birds. This review presents the current state of the art of bipedal walking robots based on natural bipedal movements (human and bird) as well as on innovative synthetic solutions. Firstly, an overview of the scientific analysis of human gait is provided as a basis for the design of bipedal robots. The full human gait cycle that consists of two main phases is analysed and the attention is paid to the problem of balance and stability, especially in the single support phase when the biped
... Show MoreIn this paper, a theoretical study to the effect of journal misalignment on the static characteristics of oil filled porous journal bearing when lubricated with couple stress fluid has been carried out.
The analytical model used through this work is for a bearing with isotropic permeability. Considering isotropic permeability the Reynolds' equation for the oil film is modified to include a so – called filter term and the effect of fluid coupled stress. The pressure equation for the porous medium is obtained from Darcy's law and continuity equation. The equation which was used to evaluate the oil film thickness was modified to include the effect of possible misalignment in longitudinal and transverse directions. The governing eq
... Show MoreThe present study investigates the notion of untranslatability where the concept of equivalence is reconsidered since the misconceptions, related to the said concept, inevitably lead to the emergence of untranslatability. Identifying equivalence as relative, approximate and necessary identity makes the notion of untranslatability a mere theorization. The objectives of the present study are (1) to investigate the notion of untranslatability in terms of the misconceptions associated with the concept of equivalence (2) to examine the possibility of translatability from Arabic into English focusing on culture-bound euphemistic expressions in the Quran as an area of challenge in translation. Data on the translation of culture-bound euphemistic e
... Show MoreOne of the most common procedures in oral surgery is the removal of impacted mandibular third molars, often followed by pain, swelling, alveolitis, and trismus. Purpose. To compare the outcomes of the intrasocket application of 1% hyaluronic acid oral gel (HA) and advanced platelet-rich fibrin (A-PRF) on the expected postoperative complications, pain, swelling, and trismus follow the surgical extraction of the impacted mandibular third molar. Material and Methods. A randomized controlled trial was conducted at the Oral and Maxillofacial Surgery Unit, Dental Teaching Hospital. Healthy patients who required surgical removal of the impacted mandibular third molar were divided randomly into three groups. The extraction site of the group
... Show MoreThe impact of applying the K-W-L self-scheduling technique on first-year intermediate students' learning of basic volleyball skills, Ayad Ali Hussein*, Israa Fouad Salih
. In recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction a
... Show MoreIn recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction acc
... Show MoreThis study had succeeded in producing a new graphical representation of James abacus called nested chain abacus. Nested chain abacus provides a unique mathematical expression to encode each tile (image) using a partition theory where each form or shape of tile will be associated with exactly one partition.Furthermore, an algorithm of nested chain abacus movement will be constructed, which can be applied in tiling theory.
This work describes an experimental setup to evaluate the photodynamictoxicity of 650 nm diode laser and 532 nm Frequency-doubled Q-Switched Nd:YAG laser on the growth of Candida albicans as well as the potential fungicidal effect when combining the laser irradiation with specific photosensitizers namely methylene blue, toluidine blue, acridine orange and safranin O. In this study the findings showed that the number of colony-forming units per millilitre (CFU/ml) of C. albicans decreased with increasing exposure time. In particular in the case of the frequency doubled Nd:YAG laser combined with safranin O, the best lethal effect occurred at 11 minutes exposure time with 2.26 J/cm² energy density (89.18% reduction) in comparison with the
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