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Exploring the Challenges of Diagnosing Thyroid Disease with Imbalanced Data and Machine Learning: A Systematic Literature Review
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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

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Publication Date
Tue May 24 2022
Journal Name
Analytical Science& Technology
A Review: Synthesis and characterization of metals complexes with paracetamol drug
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In this review, previous studies on the synthesis and characterization of the metal Complexes with paracetamol by elemental analysis, thermal analysis, (IR, NMR and UV-Vis (spectroscopy and conductivity. In reviewing these studies, the authors found that paracetamol can be coordinated through the pair of electrons on the hydroxyl O-atom, carbonyl O-atom, and N-atom of the amide group. If the paracetamol was a monodentate ligand, it will be coordinated by one of the following atoms O-hydroxyl, O-carbonyl or N-amide. But if the paracetamol was bidentate, it is coordinated by atoms (O-carbonyl and N-amide), (O-hydroxyl and N-amide) or (O-carbonyl and O-hydroxyl). The authors also found that free paracetamol and its complexes have antimicrobial

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Publication Date
Tue Sep 30 2025
Journal Name
Medical Journal Of Babylon
Pompe Disease (A Rare Metabolic Disease) in Basrah, the South of Iraq
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Pompe disease is a progressive, multisystemic, debilitating, often fatal neuromuscular disease caused by a pathogenic variant in the acid α-glucosidase gene leading to GAA enzyme deficiency and lysosomal glycogen accumulation. Objectives: This study aimed to determine the prevalence of early onset Pompe disease in Basra, using the dried blood spot (DBS) as a screening tool, also to determine the spectrum of presentation. Materials and Methods: In a prospective study conducted in Basrah, Iraq, from October 2021 to September 2023, all infants with a family member diagnosed as a case of Pompe disease, hypotonia, or ventricular hypertrophy referred to the pediatric cardiology unit in Basra Cardiac Hospital were subjected to echocardiographic e

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Publication Date
Wed Feb 01 2023
Journal Name
Baghdad Science Journal
Revision of some Biomarkers with Cytokines in Breast Cancer
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Breast cancer is the most repeatedly detected cancer category and the second reason cause of cancer-linked deaths among women worldwide. Tumor bio-indictor is a term utilized to describe possible indicators for carcinoma diagnosis, development and progression. The goal of this study is to evaluate part of some cytokines and biomarkers for both serum and saliva samples in breast cancer then estimate their potential value in the early diagnosis of breast cancer by doing more researches in saliva, and utilizing saliva instead of blood (serum and plasma) in sample collection from patients. Serum and salivary samples were taken from 72 patients with breast cancer and 45 healthy controls, in order to investigate the following

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Publication Date
Sat Oct 01 2022
Journal Name
Baghdad Science Journal
A Crime Data Analysis of Prediction Based on Classification Approaches
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Crime is considered as an unlawful activity of all kinds and it is punished by law. Crimes have an impact on a society's quality of life and economic development. With a large rise in crime globally, there is a necessity to analyze crime data to bring down the rate of crime. This encourages the police and people to occupy the required measures and more effectively restricting the crimes. The purpose of this research is to develop predictive models that can aid in crime pattern analysis and thus support the Boston department's crime prevention efforts. The geographical location factor has been adopted in our model, and this is due to its being an influential factor in several situations, whether it is traveling to a specific area or livin

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Publication Date
Sun Sep 06 2020
Journal Name
European Journal Of Dental Education
Evaluation of technology‐based learning by dental students during the pandemic outbreak of coronavirus disease 2019
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Publication Date
Tue Dec 20 2022
Journal Name
2022 International Conference On Computer And Applications (icca)
Improve Data Mining Techniques with a High-Performance Cluster
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Publication Date
Fri Jul 30 2021
Journal Name
Iraqi Journal For Electrical And Electronic Engineering
EEG Motor-Imagery BCI System Based on Maximum Overlap Discrete Wavelet Transform (MODWT) and Machine learning algorithm
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The ability of the human brain to communicate with its environment has become a reality through the use of a Brain-Computer Interface (BCI)-based mechanism. Electroencephalography (EEG) has gained popularity as a non-invasive way of brain connection. Traditionally, the devices were used in clinical settings to detect various brain diseases. However, as technology advances, companies such as Emotiv and NeuroSky are developing low-cost, easily portable EEG-based consumer-grade devices that can be used in various application domains such as gaming, education. This article discusses the parts in which the EEG has been applied and how it has proven beneficial for those with severe motor disorders, rehabilitation, and as a form of communi

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Publication Date
Wed Apr 20 2011
Journal Name
Journal Of Al-qadisiyah For Computer Science And Mathematics
Chaos in a harvested prey-predator model with infectious disease in the prey
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A harvested prey-predator model with infectious disease in preyis investigated. It is assumed that the predator feeds on the infected prey only according to Holling type-II functional response. The existence, uniqueness and boundedness of the solution of the model are investigated. The local stability analysis of the harvested prey-predator model is carried out. The necessary and sufficient conditions for the persistence of the model are also obtained. Finally, the global dynamics of this model is investigated analytically as well as numerically. It is observed that, the model have different types of dynamical behaviors including chaos.

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Publication Date
Tue Nov 06 2018
Journal Name
Iraqi National Journal Of Nursing Specialties
Correlation between Thyroid-related Hormones and Preeclampsia
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Objectives: In order to highlight the TSH and thyroid hormones levels in preeclamptic and healthy pregnant
women.
Methodology: Ninety patients with preeclampsia were divided into two groups according to the severity of
disease; those with mild disease (37 patients) and those with a severe form (53 patients). A separate group of 30
normal women were included as a normal control group. Venus blood samples were collected from all groups
and the serum was obtained for hormone analysis by ELISA test. Results are expressed using SPSS for window
version 11.0.
Results: Mean serum TSH levels were significantly increased in both of mild and severe preeclampsia compared
with normal pregnancy, and T3 serum level showed a sign

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Publication Date
Sun Nov 01 2020
Journal Name
Iop Conference Series: Materials Science And Engineering
Development of an Optimized Botnet Detection Framework based on Filters of Features and Machine Learning Classifiers using CICIDS2017 Dataset
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Abstract<p>Botnet is a malicious activity that tries to disrupt traffic of service in a server or network and causes great harm to the network. In modern years, Botnets became one of the threads that constantly evolving. IDS (intrusion detection system) is one type of solutions used to detect anomalies of networks and played an increasing role in the computer security and information systems. It follows different events in computer to decide to occur an intrusion or not, and it used to build a strategic decision for security purposes. The current paper <italic>suggests</italic> a hybrid detection Botnet model using machine learning approach, performed and analyzed to detect Botnet atta</p> ... Show More
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