Coronavirus disease (COVID-19) cases analysis using machine-learning applications (2021-05-21T00:00:00.000000Z)

TL;DR

The findings show that machine learning can produce an important role in COVID-19 investigations, prediction, and discrimination and can be involved in the health provider programs and plans to assess and triage the CO VID-19 cases.

Abstract

Today world thinks about coronavirus disease that which means all even this pandemic disease is not unique. The purpose of this study is to detect the role of machine-learning applications and algorithms in investigating and various purposes that deals with COVID-19. Review of the studies that had been published during 2020 and were related to this topic by seeking in Science Direct, Springer, Hindawi, and MDPI using COVID-19, machine learning, supervised learning, and unsupervised learning as keywords. The total articles obtained were 16,306 overall but after limitation; only 14 researches of these articles were included in this study. Our findings show that machine learning can produce an important role in COVID-19 investigations, prediction, and discrimination. In conclusion, machine learning can be involved in the health provider programs and plans to assess and triage the COVID-19 cases. Supervised learning showed better results than other Unsupervised learning algorithms by having 92.9% testing accuracy. In the future recurrent supervised learning can be utilized for superior accuracy.

Authors

Ameer Sardar Kwekha-Rashid

1 papers

H. N. Abduljabbar

1 papers

Bilal S. A. Alhayani

1 papers

TL;DR

Abstract

Authors

References40 items

A systematic review on recent trends and perspectives of biosensors in food industries

Rapid determination of remdesivir (SARS-CoV-2 drug) in human plasma for therapeutic drug monitoring in COVID-19-Patients

Overview on routing and resource allocation based machine learning in optical networks

Is Machine Learning a Better Way to Identify COVID-19 Patients Who Might Benefit from Hydroxychloroquine Treatment?—The IDENTIFY Trial

Development of a machine learning algorithm to predict intubation among hospitalized patients with COVID-19

Applications of artificial intelligence in battling against covid-19: A literature review

Machine learning for coronavirus covid-19 detection from chest x-rays

Evaluation of Country Dietary Habits Using Machine Learning Techniques in Relation to Deaths from COVID-19

Perceived Stress and Its Associated Factors during COVID-19 among Healthcare Providers in Ethiopia: A Cross-Sectional Study

Development and clinical implementation of tailored image analysis tools for COVID-19 in the midst of the pandemic: The synergetic effect of an open, clinically embedded software development platform and machine learning

Prediction of the final size for COVID-19 epidemic using machine learning: A case study of Egypt

Predicting Psychological Distress Amid the COVID-19 Pandemic by Machine Learning: Discrimination and Coping Mechanisms of Korean Immigrants in the U.S.

A systematic review on recent trends in transmission, diagnosis, prevention and imaging features of COVID-19

Utilization of machine-learning models to accurately predict the risk for critical COVID-19

A multimethod approach for county-scale geospatial analysis of emerging infectious diseases: a cross-sectional case study of COVID-19 incidence in Germany

Prediction of respiratory decompensation in Covid-19 patients using machine learning: The READY trial

Chest CT for triage during COVID-19 on the emergency department: myth or truth?

Rapid Emergence of SARS-CoV-2 in the Greater New York Metropolitan Area: Geolocation, Demographics, Positivity Rates, and Hospitalization for 46 793 Persons Tested by Northwell Health

Machine learning based approaches for detecting COVID-19 using clinical text data

COVID-19 and frequent use of hand sanitizers; human health and environmental hazards by exposure pathways

Machine Learning Maps Research Needs in COVID-19 Literature

Artificial Intelligence and COVID-19: Deep Learning Approaches for Diagnosis and Treatment

Artificial Neural Network Modeling of Novel Coronavirus (COVID-19) Incidence Rates across the Continental United States

Detection of COVID-19 Infection from Routine Blood Exams with Machine Learning: A Feasibility Study

Automatic Detection of Coronavirus Disease (COVID-19) in X-ray and CT Images: A Machine Learning Based Approach

Forecasting Models for Coronavirus Disease (COVID-19): A Survey of the State-of-the-Art

Julia Language in Machine Learning: Algorithms, Applications, and Open Issues

Covid-19: identifying and isolating asymptomatic people helped eliminate virus in Italian village

A new coronavirus associated with human respiratory disease in China

Exploring the Potential of Artificial Intelligence and Machine Learning to Combat COVID-19 and Existing Opportunities for LMIC: A Scoping Review

Novel GIS Based Machine Learning Algorithms for Shallow Landslide Susceptibility Mapping

Pattern Recognition and Machine Learning

The Elements of Statistical Learning: Data Mining, Inference, and Prediction

An Classification–Detection Approach of COVID-19 Based on Chest X-ray and CT by Using Keras Pre-Trained Deep Learning Models

Machine Learning nd Classical Forecasting Methods Based Decision Support Systems for COVID-19

Intelligent Cloud Based Heart Disease Prediction System Empowered with Supervised Machine Learning

Applying Feature-Weighted Gradient Decent K-Nearest Neighbor to Select Promising Projects for Scientific Funding

Surgical Outcome Prediction in Total Knee Arthroplasty using Machine Learning

The Elements of Statistical Learning: Data Mining, Inference, and Prediction

Publisher's Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations

Field of Study

Journal Information

Name

Page

Volume

Venue Information

Name

Type

URL

Alternate Names