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
Objectives: The aim of the study is to evaluate the information of caregivers concerned emergency care for the elderly and to identify the relationship between caregiver information and their educational level, years of service and training courses. Methodology: A quasi-experimental study was conducted in the Geriatric Care Home in Baghdad City (the governmental and private geriatric care home ) for the period from October, 14th , 2018 to March, 20th , 2019 to find the effectiveness of the instructional program on caregivers knowledge about emergency care for the elderly.. A purposive sample (non-probability) was consisting of (30) males and females caregivers, the sample was selected from geriatric care home in Baghdad city .To implemen
... Show MoreInhalation of Staphylococcal Enterotoxin B (SEB) is known to induce acute lung injury (ALI) and studies from our laboratory have shown that THC, a psychoactive ingredient found in Cannabis sativa, can attenuate the ALI. In the current study, we investigated the role played by lung microbiota in ALI with or without THC treatment. A dual-dose of SEB was given to C3H/HeJ mice, which were then treated either with vehicle or THC. SEB-administration caused ALI and 100% mortality while all THC-treated mice survived and suppressed the inflammation in the lungs. Furthermore, lung microbiota was collected and 16S rRNA sequencing was performed. The data were analyzed to determine the alpha and b
This study presents a detailed morphology and taxonomic study of Polysiphonia subtilissima collected from Abdul Rehman Goth, Karachi coast, Pakistan. Polysiphonia is a filamentous heterotrichous red algae, characterized by its branching structures and attachment mechanisms. P. subtilissima is notable for its broad salinity tolerance and wide distribution across marine and freshwater ecosystems. This research provides an in-depth examination of the internal and external structures of P. subtilissima, contributing to its systematic study and documenting its first recorded occurrence in Pakistani coastal areas, bordering the northern Arabian Sea. The findings enhance the understanding of the species taxonomy and its ecological role in
... Show MoreThis study offers numerical simulation results using the ABAQUS/CAE version 2019 finite element computer application to examine the performance, and residual strength of eight recycle aggregate RC one-way slabs. Six strengthened by NSM CFRP plates were presented to study the impact of several parameters on their structural behavior. The experimental results of four selected slabs under monotonic load, plus one slab under repeated load, were validated numerically. Then the numerical analysis was extended to different parameters investigation, such as the impact of added CFRP length on ultimate load capacity and load-deflection response and the impact of concrete compressive strength value on the structural performance of
... Show MoreIn the present study, a total of 272 freshwater fishes belonging to three species namely: Cyprinus carpio, Barbus xanthopterus and Aspius vorax, were collected from Euphrates river at Al-Haklania distrct, Al-Anbar province during the period from August 2008 till the end of July 2009, by using gill nets and cast nets. Fishes were survyed for intestinal parasitic worms. The investigation revealed the infectation of these fishes with four parasitic species: the digenetic trematode Aspidogaster limacoides from the intestine of C. carpio, B. xanthopterus and A. vorax, larval nematode Contracaecum spp. from the body cavity of C. carpio and the external surface of intestine of B
... Show MoreFinding a path solution in a dynamic environment represents a challenge for the robotics researchers, furthermore, it is the main issue for autonomous robots and manipulators since nowadays the world is looking forward to this challenge. The collision free path for robot in an environment with moving obstacles such as different objects, humans, animals or other robots is considered as an actual problem that needs to be solved. In addition, the local minima and sharp edges are the most common problems in all path planning algorithms. The main objective of this work is to overcome these problems by demonstrating the robot path planning and obstacle avoidance using D star (D*) algorithm based on Particle Swarm Optimization (PSO)
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