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
Background: The beliefs of pharmacy students in their curriculum may be critical to the success of medical education and the development of global health competences. Objective: To assess the beliefs, attitudes, and obstacles of PharmD students at the College of Pharmacy, University of Baghdad, during their first year in the newly adopted PharmD program. Method: In-depth qualitative interviews were conducted using flexible probing approaches. A sample of fourth-year PharmD students from the University of Baghdad's College of Pharmacy was selected using a purposive sampling method. The gathered data was analyzed using a thematic content analysis approach. Results: 40% of participants applied for the program because they believed it w
... Show MoreBackground: Medication reconciliation can include medication reviewing and providing counseling and a list of all the medications during every transition of care. Objectives: to explore in-depth the perspectives of Iraqi physicians and pharmacists regarding the necessity of medication reconciliation at hospital discharge and identify the possible benefits and challenges that could face its implementation. Subjects and Methods: A qualitative study included semi-structured interviews with pharmacists and physicians working at a public teaching hospital in Iraq. The interviews were conducted face-to-face from February to March 2023. Thematic analysis was used to analyze the qualitative data generated from the interviews. Results: In th
... Show MoreMT Suhail, SA Hussein, MN Abdulhussein, WQ Abdaullateef, M khairallah Aid…, Migration Letters, 2024
The rapid increase in the number of older people with Alzheimer’s disease (AD) and other forms of dementia represents one of the major challenges to the health and social care systems because of a large number of people affected. Early detection of AD makes it possible for patients to access appropriate services and to benefit from new treatments and therapies, as and when they become available, and to plan for the future. The onset of AD starts many years before the clinical symptoms become clear. A biomarker that can measure the brain changes in this period would be useful for early diagnosis of AD. Potentially, the electroencephalogram (EEG) can play a valuable role in early detection of AD. Damage caused to the brain due to AD leads t
... Show MoreLarge amounts of plasma, the universe’s fourth most common kind of stuff, may be found across our galaxy and other galaxies. There are four types of matter in the cosmos, and plasma is the most common. By heating the compressed air or inert gases to create negatively and positively charged particles known as ions, electrically neutral particles in their natural state are formed. Many scientists are currently focusing their efforts on the development of artificial plasma and the possible advantages it may have for humankind in the near future. In the literature, there is a scarcity of information regarding plasma applications. It’s the goal of this page to describe particular methods for creating and using plasma, which may be us
... Show MoreAbstractBackground:Reduced glomeular filtration rate isassociated with increasedmorbidity in patientswith coronary arterydisease.Objectives :To analyze the declining eGFR andmortality risks in a patients with Chronic KidneyDisease and have had Coronary Artery Diseaseincluding risk factors .Patientsand Methods:The study included (160)patientsbetween the ages of 16 and 87years.Glomerular filtration rate was estimated (eGFR)using the Modification of Diet in Renal Diseaseequationand was categorized in the ranges<60 mL· min−1 per 1.73 m2and≥ 60 ml/min/1.73 m2.Baseline risk factors were analyzed by category ofeGFR,.The studied patients in emergencydepartment, were investigatedusing Coxproportional hazard models adjusting for traditiona
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