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
— To identify the effect of deep learning strategy on mathematics achievement and practical intelligence among secondary school students during the 2022/2023 academic year. In the research, the experimental research method with two groups (experimental and control) with a post-test were adopted. The research community is represented by the female students of the fifth scientific grade from the first Karkh Education Directorate. (61) female students were intentionally chosen, and they were divided into two groups: an experimental group (30) students who were taught according to the proposed strategy, and a control group (31) students who were taught according to the usual method. For the purpose of collecting data for the experimen
... Show MoreSince the Internet has been more widely used and more people have access to multimedia content, copyright hacking, and piracy have risen. By the use of watermarking techniques, security, asset protection, and authentication have all been made possible. In this paper, a comparison between fragile and robust watermarking techniques has been presented to benefit them in recent studies to increase the level of security of critical media. A new technique has been suggested when adding an embedded value (129) to each pixel of the cover image and representing it as a key to thwart the attacker, increase security, rise imperceptibility, and make the system faster in detecting the tamper from unauthorized users. Using the two watermarking ty
... Show MoreInfection with cryptosporidiosis endangers the lives of many people with immunodeficiency, especially HIV patients. Nitazoxanide is one of the main therapeutic drugs used to treat cryptosporidiosis. However, it is poorly soluble in water, which restricts its usefulness and efficacy in immunocompromised patients. Surfactants have an amphiphilic character which indicates their ability to improve the water solubility of the hydrophobic drugs. Our research concerns the synthesis of new cationic Gemini surfactants that have the ability to improve the solubility of the drug Nanazoxide. So, we synthesized cationic Gemini surfactants. N1,N1,N3,N3-tetramethyl-N1,N3-bis(2-octadecanamidoethyl)propane-1,3-diaminium bromide (CGSPS18) and 2,2‘-(etha
... Show MoreKE Sharquie, MA Al-Dhalimi, AA Noaimi, HA Al-Sultany, Journal of Cosmetics, Dermatological Sciences and Applications, 2012 - Cited by 2
This study, which was conducted in the city of Mosul, through collected 1200 samples from the stool of patients with diarrhea attending hospitals and private clinics for the period from the beginning of January 2019 to the end of December 2019, those whose ages ranged from less than a year-60 year, and for both sexes and by reality 700 samples stool for males and 500 samples stool for females. Samples were collected in clean, sterile, and sealed 40ml plastic bottles. Patient information is noted, name of the parasite, history, sex, age, address. The result showed that climate and temperature have a significant effect on increase the incidence of intestinal parasites through the direct effect on the increase in infection rate. This effect wa
... Show MoreAlzheimer’s disease (AD) is a progressive disorder that affects cognitive brain functions and starts many years before its clinical manifestations. A biomarker that provides a quantitative measure of changes in the brain due to AD in the early stages would be useful for early diagnosis of AD, but this would involve dealing with large numbers of people because up to 50% of dementia sufferers do not receive formal diagnosis. Thus, there is a need for accurate, low-cost, and easy to use biomarkers that could be used to detect AD in its early stages. Potentially, electroencephalogram (EEG) based biomarkers can play a vital role in early diagnosis of AD as they can fulfill these needs. This is a cross-sectional study that aims to demon
... Show MoreObjective This research investigates Breast Cancer real data for Iraqi women, these data are acquired manually from several Iraqi Hospitals of early detection for Breast Cancer. Data mining techniques are used to discover the hidden knowledge, unexpected patterns, and new rules from the dataset, which implies a large number of attributes. Methods Data mining techniques manipulate the redundant or simply irrelevant attributes to discover interesting patterns. However, the dataset is processed via Weka (The Waikato Environment for Knowledge Analysis) platform. The OneR technique is used as a machine learning classifier to evaluate the attribute worthy according to the class value. Results The evaluation is performed using
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