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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
Thu Aug 01 2024
Journal Name
Advances In Science And Technology Research Journal
Power Predicting for Power Take-Off Shaft of a Disc Maize Silage Harvester Using Machine Learning
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Publication Date
Sat Dec 31 2022
Journal Name
Al-kindy College Medical Journal
Changing the Trends in Surgery during the COVID-19 Times: An Experience from the Eastern Uttar Pradesh State, India: CHANGING TRENDS IN SURGERY DURING COVID TIMES
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Background: The COVID-19 pandemic has an immense effect not only on the social and economic lives of people but also on the surgical lives of surgeons, residents, nursing staff, and patients as well as ground level staff. Amidst this COVID pandemic, emergency surgeries were being done but at a decreased rate, whereas elective cases depended on the will of hospitals, surgeons, and patients. Study aims to promulgate a "Neo–Surgical Check Box" by amalgamating the WHO surgical checklist and the results obtained from the questionnaires.

Subjects and Methods: After receiving ethical clearance from the Institute Ethical Committee, an online questionnaire with 50 questions divided into

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Publication Date
Sat Sep 30 2017
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Permeability Prediction By Classical and Flow Zone Indictor (FZI) Methods for an Iraqi Gas Field
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The permeability is the most important parameter that indicates how efficient the reservoir fluids flow through the rock pores to the wellbore. Well-log evaluation and core measurements techniques are typically used to estimate it. In this paper, the permeability has been predicted by using classical and Flow zone indicator methods. A comparison between the two methods shows the superiority of the FZI method correlations, these correlations can be used to estimate permeability in un-cored wells with a good approximation.

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Publication Date
Fri Dec 01 2023
Journal Name
Slas Discovery
Role Of Vaccines Against COVID-19 Pandemic
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Publication Date
Fri Jan 27 2023
Journal Name
Research Journal Of Pharmacy And Technology
Physical human Activity, Immunity and COVID-19
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Background: The global threat of COVID-19 outbreak and on the 11 March 2020, WHO acknowledged that the virus would likely spread to all countries across the globe and declared the coronavirus outbreak a pandemic which is the fifth pandemic since 20 century and this has brought human lives to a sudden and complete lockdown and the confirmed cases of this disease and deaths continue to rise in spite of people around the world are taking important actions to mitigate and decrease transmission and save lives. Objectives: To assess the effect of exercise and physical activity on the immunity against COVID-19. Methods: Collected electronic databases including (Medline, EMBASE, Google Scholar, PubMed and Web of Science) were searched with

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Publication Date
Tue Nov 09 2021
Journal Name
Open Access Macedonian Journal Of Medical Sciences
COVID-19 Vaccine Hesitancy and Acceptance among Medical Students: An Online Cross-sectional Study in Iraq
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BACKGROUND: Vaccine hesitancy and reluctant had an important obstacle in achieving protection and population immunity against coronavirus disease 19 (COVID-19). It is essential to achieve high COVID-19 vaccination acceptance rates among medical students and health care workers to provide recommendations and counseling vaccine hesitant population. AIM: This study aims to identify level of COVID-19 hesitancy, attitude, knowledge, and factors that affect vaccination decision. MATERIALS AND METHODS: A cross-sectional study was done among medical students in Al-Kindy College of Medicine, University of Baghdad, Baghdad, Iraq. Data collection was done through an online Google Forms questionnaire during 2021 from 810 medical students.

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Publication Date
Sat Jun 01 2024
Journal Name
Journal Of Ecological Engineering
Using Machine Learning Algorithms to Predict the Sweetness of Bananas at Different Drying Times
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Publication Date
Sun Jan 01 2023
Journal Name
Journal Of Intelligent Systems
A study on predicting crime rates through machine learning and data mining using text
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Abstract<p>Crime is a threat to any nation’s security administration and jurisdiction. Therefore, crime analysis becomes increasingly important because it assigns the time and place based on the collected spatial and temporal data. However, old techniques, such as paperwork, investigative judges, and statistical analysis, are not efficient enough to predict the accurate time and location where the crime had taken place. But when machine learning and data mining methods were deployed in crime analysis, crime analysis and predication accuracy increased dramatically. In this study, various types of criminal analysis and prediction using several machine learning and data mining techniques, based o</p> ... Show More
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Publication Date
Fri Oct 31 2025
Journal Name
Mathematical Modelling Of Engineering Problems
Heterogeneous Traffic Management in SDN-Enabled Data Center Network Using Machine Learning-SPIKE Model
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Software-Defined Networking (SDN) has evolved network management by detaching the control plane from the data forwarding plane, resulting in unparalleled flexibility and efficiency in network administration. However, the heterogeneity of traffic in SDN presents issues in achieving Quality of Service (QoS) demands and efficiently managing network resources. SDN traffic flows are often divided into elephant flows (EFs) and mice flows (MFs). EFs, which are distinguished by their huge packet sizes and long durations, account for a small amount of total traffic but require disproportionate network resources, thus causing congestion and delays for smaller MFs. MFs, on the other hand, have a short lifetime and are latency-sensitive, but they accou

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Publication Date
Fri Oct 14 2022
Journal Name
المجلة العراقية لعلوم التربة
REVIEW: USING MACHINE VISION AND DEEP LEARINING IN AUTOMATED SORTING OF LOCAL LEMONS
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Sorting and grading agricultural crops using manual sorting is a cumbersome and arduous process, in addition to the high costs and increased labor, as well as the low quality of sorting and grading compared to automatic sorting. the importance of deep learning, which includes the artificial neural network in prediction, also shows the importance of automated sorting in terms of efficiency, quality, and accuracy of sorting and grading. artificial neural network in predicting values and choosing what is good and suitable for agricultural crops, especially local lemons.