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The Role of Artificial Intelligence in Diagnosing Heart Disease in Humans: A Review
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The electrical activity of the heart and the electrocardiogram (ECG) signal are fundamentally related. In the study that has been published, the ECG signal has been examined and used for a number of applications. The monitoring of heart rate and the analysis of heart rhythm patterns, the detection and diagnosis of cardiac diseases, the identification of emotional states, and the use of biometric identification methods are a few examples of applications in the field. Several various phases may be involved in the analysis of electrocardiogram (ECG) data, depending on the type of study being done. Preprocessing, feature extraction, feature selection, feature modification, and classification are frequently included in these stages. Every stage must be finished in order for the analysis to go smoothly. Additionally, accurate success measures and the creation of an acceptable ECG signal database are prerequisites for the analysis of electrocardiogram (ECG) signals. Identification and diagnosis of various cardiac illnesses depend heavily on the ECG segmentation and feature extraction procedure. Electrocardiogram (ECG) signals are frequently obtained for a variety of purposes, including the diagnosis of cardiovascular conditions, the identification of arrhythmias, the provision of physiological feedback, the detection of sleep apnea, routine patient monitoring, the prediction of sudden cardiac arrest, and the creation of systems for identifying vital signs, emotional states, and physical activities. The ECG has been widely used for the diagnosis and prognosis of a variety of heart diseases. Currently, a range of cardiac diseases can be accurately identified by computerized automated reports, which can then generate an automated report. This academic paper aims to provide an overview of the most important problems associated with using deep learning and machine learning to diagnose diseases based on electrocardiography, as well as a review of research on these techniques and methods and a discussion of the major data sets used by researchers.

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Publication Date
Fri Jun 16 2023
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
An update on Nanoparticle Formulation Design of Piperine to Improve its Oral bioavailability: A Review
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Piperine, a crystalline alkaloid compound isolated from Piper nigrum, piper longum, and other types of piper, has had many fabulous pharmacological advantages for preventing and treating some specific diseases, such as analgesic, anti-inflammatory, hepatoprotective, antimetastatic, antithyroid, immunomodulatory, antitumor, rheumatoid arthritis, osteoarthritis, Alzheimer's, and improving the bioavailability of other drugs. However, its potential for clinical use through oral usage is hindered by water solubility and poor bioavailability. The low level of oral bioavailability is caused by low solubility in water and is photosensitive, susceptible to isomerization by UV light, which causes piperine concentration to decrease. Many different

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Publication Date
Tue Feb 04 2025
Journal Name
Journal Of Baghdad College Of Dentistry
Establishment of the possible association between the presence of Helicobacter pylori in the saliva and gastric biopsy by using polymerase chain reaction technique in association with oral manifestation of peptic ulcer disease
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Background: Helicobacter pylori are important gastrointestinal pathogen associated with gastritis, peptic ulcers, and an increased risk of gastric carcinoma. There are several popular methods for detection of H. pylori (invasive and non-invasive methods) each having its own advantages, disadvantages, and limitations, and by using PCR technique the ability to detect H. pylori in saliva samples offers a potential for an alternative test for detection of this microorganism. Materials and methods: The study sample consists of fifty participants of both genders, who undergo Oesophageo-gastrodudenoscopy at the Gastroenterology Department of Al-Kindy Teaching Hospital Baghdad/ Iraq, during five months period from January 2014 to May 2014. They we

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Publication Date
Tue Dec 20 2022
Journal Name
International Journal Of Emerging Technologies In Learning (ijet)
Effect of Augmented Reality Technology on Spatial Intelligence among High School Students
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Spatial Intelligence is a mental ability to understand and solve real-world problems. These visual-spatial representations are fundamental in learning various "STEM" topics, like digital drawing, art presentations, creating graphical representations, 2D designs. Opportunity to interact with real and/or virtual objects. It is a good opportunity in applying new techniques such as the augmenter, which is able to clarify mathematical tables, concepts and generalizations greatly to the visualization, understanding and mastery of concepts mathematically. The purpose of the research is to investigate impact of using AR technology in developing spatial intelligence for secondary school students, Baghdad. The quasi-experimental design was us

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Publication Date
Fri Jan 01 2021
Journal Name
Ieee Access
Proposition of New Ensemble Data-Intelligence Models for Surface Water Quality Prediction
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Publication Date
Wed May 22 2024
Journal Name
Journal Of Angiotherapy
Immune Cytokines IFN-γ, TGF-β, TNF-α, and IL-1β Modulate the Pathophysiological Markers in Idiopathic Parkinson’s Disease
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Background: Parkinson's disease (PD) is a neurodegenerative aging disease, with idiopathic PD being most common. Gastrointestinal tract disorders (GITD) and microbiota changes may trigger idiopathic PD. Neurotoxins from microbiota can travel from the gut to the brain via the brain-gut axis (BGA), leading to α-syn protein misfolding and dopaminergic neuron death. Methods: The aim of the current study was to investigate the link between PD and GITD by measuring several biochemical and immunological markers in 142 patients. The biochemical markers measured were vitamins B6, B12, and D, calcium, serotonin, ghrelin, dopamine, and α-syn protein. The immunological markers included transforming growth factor-beta (TGF-β), tu

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Publication Date
Sun Jan 01 2023
Journal Name
Aip Conference Proceedings
Using the artificial TABU algorithm to estimate the semi-parametric regression function with measurement errors
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Artificial Intelligence Algorithms have been used in recent years in many scientific fields. We suggest employing artificial TABU algorithm to find the best estimate of the semi-parametric regression function with measurement errors in the explanatory variables and the dependent variable, where measurement errors appear frequently in fields such as sport, chemistry, biological sciences, medicine, and epidemiological studies, rather than an exact measurement.

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Publication Date
Thu Feb 29 2024
Journal Name
International Journal Of Design & Nature And Ecodynamics
Artificial Neural Network Assessment of Groundwater Quality for Agricultural Use in Babylon City: An Evaluation of Salinity and Ionic Composition
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Publication Date
Thu Aug 01 2019
Journal Name
Journal Of Economics And Administrative Sciences
The Role of Strategic direction in Strategic Reputation and its impact on Competitive Compressions Survey study in mobile communications companies in Iraq
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Publication Date
Tue Jan 10 2012
Journal Name
Iraqi Journal Of Science
THE IMPACT OF DISEASE AND HARVESTING ON THE DYNAMICAL BEHAVIOR OF PREY PREDATOR MODEL
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In this paper, a harvested prey-predator model involving infectious disease in prey is considered. The existence, uniqueness and boundedness of the solution are discussed. The stability analysis of all possible equilibrium points are carried out. The persistence conditions of the system are established. The behavior of the system is simulated and bifurcation diagrams are obtained for different parameters. The results show that the existence of disease and harvesting can give rise to multiple attractors, including chaos, with variations in critical parameters.

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Publication Date
Fri Jan 01 2021
Journal Name
Review Of International Geographical Education Online
Role of ERP Systems in Improving Human Resources Management Processes
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This study investigates the role of Enterprise Resources Planning (ERP) systems in improving human resources management (HRM) processes. The rapid environmental changes led to increased demand on the ERP systems, which have changed the manual effort to technology-based processes, providing solutions focusing on the integration of all departments to achieve goals for the entire organization. HRM processes are mainly made up of two classes: strategic and operational HRM. An ERP system works to integrate both of them, making HRM processes more efficient, effective and feasible to provide support to the organization as a whole (inside and outside). In this article, a modest framework is proposed to describe HRM process integrity in relation to

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