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Covid-19 Prediction using Machine Learning Methods: An Article Review
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The COVID-19 pandemic has necessitated new methods for controlling the spread of the virus, and machine learning (ML) holds promise in this regard. Our study aims to explore the latest ML algorithms utilized for COVID-19 prediction, with a focus on their potential to optimize decision-making and resource allocation during peak periods of the pandemic. Our review stands out from others as it concentrates primarily on ML methods for disease prediction.To conduct this scoping review, we performed a Google Scholar literature search using "COVID-19," "prediction," and "machine learning" as keywords, with a custom range from 2020 to 2022. Of the 99 articles that were screened for eligibility, we selected 20 for the final review.Our systematic literature review demonstrates that ML-powered tools can alleviate the burden on healthcare systems. These tools can analyze significant amounts of medical data and potentially improve predictive and preventive healthcare.

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Publication Date
Fri Apr 01 2022
Journal Name
Galore International Journal Of Health Sciences And Research
Use of Flavonoids and Green Tea Extracts as Antioxidants Induced by Oxidative Stress: A Review Article
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The aim of this work is to shed light on the importance of medicinal plants, especially those that have extracts that have a direct effect on human health. The study and identification of botany is necessary because human life has become closely linked to the life of plants as food. In addition to using plants as food, primitive man did not stop at this point, but rather developed their use to hunt prey and also used toxic plant materials in wars. With the passage of time, the ancient man was able to link the wild plants that cover the surface of the earth and the diseases that afflict him, so he used these plants or Parts of it are for treatment. A medicinal plant is defined as one or more of its parts that contain one or more chemicals in

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Publication Date
Fri Apr 22 2022
Journal Name
Galore International Journal Of Health Sciences And Research
Use of Flavonoids and Green Tea Extracts as Antioxidants Induced by Oxidative Stress: A Review Article
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The aim of this work is to shed light on the importance of medicinal plants, especially those that have extracts that have a direct effect on human health. The study and identification of botany is necessary because human life has become closely linked to the life of plants as food . In addition to using plants as food, primitive man did not stop at this point, but rather developed their use to hunt prey and also used toxic plant materials in wars. With the passage of time, the ancient man was able to link the wild plants that cover the surface of the earth and the diseases that afflict him, so he used these plants or Parts of it are for treatment. A medicinal plant is defined as one or more of its parts that contain one or more che

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Publication Date
Fri Dec 20 2024
Journal Name
Iraqi Journal Of Pharmaceutical Sciences
Sulfur Derivatives of 1,2,4-Triazole: Recently Developed Compounds, Structure Activity Relationship, and Biological Activity: Review article
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The term of heterocyclic chemistry focuses only on heterocyclic compounds, which consider as a percentage of organic chemistry, they equal to greater than sixty-five. These compounds are widely founded in nature and most of them are important to life. In the past few years, scientist fused on 1,2,4-triazoles and their condensed heterocyclic ring due to their medicinal significance, 1,2,4-triazole containing Sulphur atom is one of the important heterocyclic moieties due to its broad range of biological activities also their derivatives can accommodate one of the alternatives as electronic effect as exchanges of the electronic density (electron donating or withdrawing) groups ; for all what mentioned above they are consider as a core

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Publication Date
Wed Nov 01 2023
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Serum Soluble Angiotensin-Converting Enzyme-2 Level and Its Potential Association With The Renin-Angiotensin-Aldosterone System in Non-Hypertensive Iraqi COVID-19 Patients: An Observational Study
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Background: The novel coronavirus disease (COVID-19) is caused by Severe acute respiratory syndrome coronavirus 2 (SARS-Cov2) which utilizes angiotensin converting enzyme2 (ACE2) to invade the host cells. This membrane-bound peptidase is widely distributed in the body; its activity antagonizes the renin-angiotensin-aldosterone system (RAAS). Once SARS-Cov2 enters the cell, it causes downregulation of ACE2, resulting in the unopposed activation of RAAS. The unregulated activity of the RAAS system can deteriorate the prognosis in COVID-19 patients. A soluble form of ACE2 (sACE2) was reported to have a role in the SARS-Cov2 invasion of the susceptible cells.

Aim of the study: This study aims to inve

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Publication Date
Tue Jul 01 2014
Journal Name
International Journal Of Artificial Intelligence And Mechatronics
Machining Polylines and Ellipses using Three-Axis CNC Milling Machine
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CNC machine is used to machine complex or simple shapes at higher speed with maximum accuracy and minimum error. In this paper a previously designed CNC control system is used to machine ellipses and polylines. The sample needs to be machined is drawn by using one of the drawing software like AUTOCAD® or 3D MAX and is saved in a well-known file format (DXF) then that file is fed to the CNC machine controller by the CNC operator then that part will be machined by the CNC machine. The CNC controller using developed algorithms that reads the DXF file feeds to the machine, extracts the shapes from the file and generates commands to move the CNC machine axes so that these shapes can be machined.

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Publication Date
Tue Dec 05 2023
Journal Name
Baghdad Science Journal
An Observation and Analysis the role of Convolutional Neural Network towards Lung Cancer Prediction
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Lung cancer is one of the most serious and prevalent diseases, causing many deaths each year. Though CT scan images are mostly used in the diagnosis of cancer, the assessment of scans is an error-prone and time-consuming task. Machine learning and AI-based models can identify and classify types of lung cancer quite accurately, which helps in the early-stage detection of lung cancer that can increase the survival rate. In this paper, Convolutional Neural Network is used to classify Adenocarcinoma, squamous cell carcinoma and normal case CT scan images from the Chest CT Scan Images Dataset using different combinations of hidden layers and parameters in CNN models. The proposed model was trained on 1000 CT Scan Images of cancerous and non-c

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Publication Date
Wed Jan 12 2022
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
A Pharmacoeconomics Study for Anticoagulants used for Hospitalized COVID-19 Patients in Al-Najaf Al-Ashraf city –Iraq(Conference Paper )#
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Abstract

Background: The novel coronavirus 2 (SARS?CoV?2) pandemic is a pulmonary disease, which leads to cardiac, hematologic, and renal complications. Anticoagulants are used for COVID-19 infected patients because the infection increases the risk of thrombosis. The world health organization (WHO), recommend prophylaxis dose of anticoagulants: (Enoxaparin or unfractionated Heparin for hospitalized patients with COVID-19 disease. This has created an urgent need to identify effective medications for COVID-19 prevention and treatment. The value of COVID-19 treatments is affected by cost-effectiveness analysis (CEA) to inform relative value and how to best maximize social welfare through eviden

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Publication Date
Mon Jun 01 2020
Journal Name
Journal Of Engineering
Arabic Sentiment Analysis (ASA) Using Deep Learning Approach
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Sentiment analysis is one of the major fields in natural language processing whose main task is to extract sentiments, opinions, attitudes, and emotions from a subjective text. And for its importance in decision making and in people's trust with reviews on web sites, there are many academic researches to address sentiment analysis problems. Deep Learning (DL) is a powerful Machine Learning (ML) technique that has emerged with its ability of feature representation and differentiating data, leading to state-of-the-art prediction results. In recent years, DL has been widely used in sentiment analysis, however, there is scarce in its implementation in the Arabic language field. Most of the previous researches address other l

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Publication Date
Fri Dec 30 2022
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Artificial Intelligent Models for Detection and Prediction of Lost Circulation Events: A Review
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Lost circulation or losses in drilling fluid is one of the most important problems in the oil and gas industry, and it appeared at the beginning of this industry, which caused many problems during the drilling process, which may lead to closing the well and stopping the drilling process. The drilling muds are relatively expensive, especially the muds that contain oil-based mud or that contain special additives, so it is not economically beneficial to waste and lose these muds. The treatment of drilling fluid losses is also somewhat expensive as a result of the wasted time that it caused, as well as the high cost of materials used in the treatment such as heavy materials, cement, and others. The best way to deal with drilling fluid losses

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Publication Date
Tue Mar 01 2022
Journal Name
Journal Of Hydrology
Boosted artificial intelligence model using improved alpha-guided grey wolf optimizer for groundwater level prediction: Comparative study and insight for federated learning technology
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