Literature DB >> 33041533

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

Mohammad-H Tayarani N1.   

Abstract

Colloquially known as coronavirus, the Severe Acute Respiratory Syndrome CoronaVirus 2 (SARS-CoV-2), that causes CoronaVirus Disease 2019 (COVID-19), has become a matter of grave concern for every country around the world. The rapid growth of the pandemic has wreaked havoc and prompted the need for immediate reactions to curb the effects. To manage the problems, many research in a variety of area of science have started studying the issue. Artificial Intelligence is among the area of science that has found great applications in tackling the problem in many aspects. Here, we perform an overview on the applications of AI in a variety of fields including diagnosis of the disease via different types of tests and symptoms, monitoring patients, identifying severity of a patient, processing covid-19 related imaging tests, epidemiology, pharmaceutical studies, etc. The aim of this paper is to perform a comprehensive survey on the applications of AI in battling against the difficulties the outbreak has caused. Thus we cover every way that AI approaches have been employed and to cover all the research until the writing of this paper. We try organize the works in a way that overall picture is comprehensible. Such a picture, although full of details, is very helpful in understand where AI sits in current pandemonium. We also tried to conclude the paper with ideas on how the problems can be tackled in a better way and provide some suggestions for future works.
© 2020 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Artificial intelligence; Artificial neural networks; Convolutional neural networks; Coronavirus; Covid-19; Deep learning; Deep neural networks; Drug discovery; Epidemiology; Evolutionary algorithms; Machine learning; SARS-CoV-2; Vaccine development

Year:  2020        PMID: 33041533      PMCID: PMC7532790          DOI: 10.1016/j.chaos.2020.110338

Source DB:  PubMed          Journal:  Chaos Solitons Fractals        ISSN: 0960-0779            Impact factor:   5.944


  64 in total

1.  Towards explainable deep neural networks (xDNN).

Authors:  Plamen Angelov; Eduardo Soares
Journal:  Neural Netw       Date:  2020-07-11

2.  Helping doctors hasten COVID-19 treatment: Towards a rescue framework for the transfusion of best convalescent plasma to the most critical patients based on biological requirements via ml and novel MCDM methods.

Authors:  O S Albahri; Jameel R Al-Obaidi; A A Zaidan; A S Albahri; B B Zaidan; Mahmood M Salih; Abdulhadi Qays; K A Dawood; R T Mohammed; Karrar Hameed Abdulkareem; A M Aleesa; A H Alamoodi; M A Chyad; Che Zalina Zulkifli
Journal:  Comput Methods Programs Biomed       Date:  2020-06-20       Impact factor: 5.428

3.  Artificial intelligence and COVID-19: A multidisciplinary approach.

Authors:  Abhimanyu S Ahuja; Vineet Pasam Reddy; Oge Marques
Journal:  Integr Med Res       Date:  2020-05-27

4.  COVID-19 detection using deep learning models to exploit Social Mimic Optimization and structured chest X-ray images using fuzzy color and stacking approaches.

Authors:  Mesut Toğaçar; Burhan Ergen; Zafer Cömert
Journal:  Comput Biol Med       Date:  2020-05-06       Impact factor: 4.589

5.  Artificial intelligence to codify lung CT in Covid-19 patients.

Authors:  Maria Paola Belfiore; Fabrizio Urraro; Roberta Grassi; Giuliana Giacobbe; Gianluigi Patelli; Salvatore Cappabianca; Alfonso Reginelli
Journal:  Radiol Med       Date:  2020-05-04       Impact factor: 3.469

6.  Can artificial intelligence identify effective COVID-19 therapies?

Authors:  Michael B Schultz; Daniel Vera; David A Sinclair
Journal:  EMBO Mol Med       Date:  2020-07-07       Impact factor: 12.137

7.  Forecasting the prevalence of COVID-19 outbreak in Egypt using nonlinear autoregressive artificial neural networks.

Authors:  Amal I Saba; Ammar H Elsheikh
Journal:  Process Saf Environ Prot       Date:  2020-05-20       Impact factor: 6.158

8.  Deep-COVID: Predicting COVID-19 from chest X-ray images using deep transfer learning.

Authors:  Shervin Minaee; Rahele Kafieh; Milan Sonka; Shakib Yazdani; Ghazaleh Jamalipour Soufi
Journal:  Med Image Anal       Date:  2020-07-21       Impact factor: 8.545

9.  Building a bioelectronic medicine movement 2019: insights from leaders in industry, academia, and research.

Authors: 
Journal:  Bioelectron Med       Date:  2020-01-31
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  26 in total

1.  Review of deep learning: concepts, CNN architectures, challenges, applications, future directions.

Authors:  Laith Alzubaidi; Jinglan Zhang; Amjad J Humaidi; Ayad Al-Dujaili; Ye Duan; Omran Al-Shamma; J Santamaría; Mohammed A Fadhel; Muthana Al-Amidie; Laith Farhan
Journal:  J Big Data       Date:  2021-03-31

Review 2.  Artificial intelligence for forecasting and diagnosing COVID-19 pandemic: A focused review.

Authors:  Carmela Comito; Clara Pizzuti
Journal:  Artif Intell Med       Date:  2022-03-28       Impact factor: 7.011

3.  Coronavirus disease (COVID-19) cases analysis using machine-learning applications.

Authors:  Ameer Sardar Kwekha-Rashid; Heamn N Abduljabbar; Bilal Alhayani
Journal:  Appl Nanosci       Date:  2021-05-21       Impact factor: 3.869

4.  Overview of current state of research on the application of artificial intelligence techniques for COVID-19.

Authors:  Vijay Kumar; Dilbag Singh; Manjit Kaur; Robertas Damaševičius
Journal:  PeerJ Comput Sci       Date:  2021-05-26

5.  Densely connected convolutional networks-based COVID-19 screening model.

Authors:  Dilbag Singh; Vijay Kumar; Manjit Kaur
Journal:  Appl Intell (Dordr)       Date:  2021-02-07       Impact factor: 5.019

6.  Framework for Real-Time Detection and Identification of possible patients of COVID-19 at public places.

Authors:  Bharati Peddinti; Amir Shaikh; Bhavya K R; Nithin Kumar K C
Journal:  Biomed Signal Process Control       Date:  2021-04-01       Impact factor: 3.880

Review 7.  Application of Artificial Intelligence-Based Regression Methods in the Problem of COVID-19 Spread Prediction: A Systematic Review.

Authors:  Jelena Musulin; Sandi Baressi Šegota; Daniel Štifanić; Ivan Lorencin; Nikola Anđelić; Tijana Šušteršič; Anđela Blagojević; Nenad Filipović; Tomislav Ćabov; Elitza Markova-Car
Journal:  Int J Environ Res Public Health       Date:  2021-04-18       Impact factor: 3.390

Review 8.  Machine Learning Approaches in COVID-19 Diagnosis, Mortality, and Severity Risk Prediction: A Review.

Authors:  Norah Alballa; Isra Al-Turaiki
Journal:  Inform Med Unlocked       Date:  2021-04-03

Review 9.  Data-driven methods for present and future pandemics: Monitoring, modelling and managing.

Authors:  Teodoro Alamo; Daniel G Reina; Pablo Millán Gata; Victor M Preciado; Giulia Giordano
Journal:  Annu Rev Control       Date:  2021-06-29       Impact factor: 6.091

10.  A Hybrid Method of Covid-19 Patient Detection from Modified CT-Scan/Chest-X-Ray Images Combining Deep Convolutional Neural Network And Two- Dimensional Empirical Mode Decomposition.

Authors:  Nahian Ibn Hasan
Journal:  Comput Methods Programs Biomed Update       Date:  2021-07-23
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