Literature DB >> 33999732

A Comprehensive Study of Artificial Intelligence and Machine Learning Approaches in Confronting the Coronavirus (COVID-19) Pandemic.

Md Mijanur Rahman1, Fatema Khatun2, Ashik Uzzaman1, Sadia Islam Sami1, Md Al-Amin Bhuiyan3, Tiong Sieh Kiong4.   

Abstract

The novel coronavirus disease (COVID-19) has spread over 219 countries of the globe as a pandemic, creating alarming impacts on health care, socioeconomic environments, and international relationships. The principal objective of the study is to provide the current technological aspects of artificial intelligence (AI) and other relevant technologies and their implications for confronting COVID-19 and preventing the pandemic's dreadful effects. This article presents AI approaches that have significant contributions in the fields of health care, then highlights and categorizes their applications in confronting COVID-19, such as detection and diagnosis, data analysis and treatment procedures, research and drug development, social control and services, and the prediction of outbreaks. The study addresses the link between the technologies and the epidemics as well as the potential impacts of technology in health care with the introduction of machine learning and natural language processing tools. It is expected that this comprehensive study will support researchers in modeling health care systems and drive further studies in advanced technologies. Finally, we propose future directions in research and conclude that persuasive AI strategies, probabilistic models, and supervised learning are required to tackle future pandemic challenges.

Entities:  

Keywords:  artificial intelligence (AI); coronavirus disease (COVID-19); deep learning (DL); health care; machine learning (ML) technology

Year:  2021        PMID: 33999732     DOI: 10.1177/00207314211017469

Source DB:  PubMed          Journal:  Int J Health Serv        ISSN: 0020-7314            Impact factor:   1.663


  5 in total

Review 1.  Artificial Intelligence Applications in Health Care Practice: Scoping Review.

Authors:  Malvika Sharma; Carl Savage; Monika Nair; Ingrid Larsson; Petra Svedberg; Jens M Nygren
Journal:  J Med Internet Res       Date:  2022-10-05       Impact factor: 7.076

2.  Research on Infant Health Diagnosis and Intelligence Development Based on Machine Learning and Health Information Statistics.

Authors:  Siyu Wang; Min Li; Soo Boon Ng
Journal:  Front Public Health       Date:  2022-06-02

3.  Design of an Incremental Music Teaching and Assisted Therapy System Based on Artificial Intelligence Attention Mechanism.

Authors:  Dapeng Li; Xiaoguang Liu
Journal:  Occup Ther Int       Date:  2022-06-16       Impact factor: 1.565

4.  Demystifying machine learning for mortality prediction.

Authors:  J M Smit; M E van Genderen; M J T Reinders; D A M P J Gommers; J H Krijthe; J Van Bommel
Journal:  Crit Care       Date:  2021-12-23       Impact factor: 9.097

Review 5.  Challenges and Opportunities for Public Health Service in Oman From the COVID-19 Pandemic: Learning Lessons for a Better Future.

Authors:  Sulien Al Khalili; Amal Al Maani; Adil Al Wahaibi; Fatma Al Yaquobi; Amina Al-Jardani; Khalid Al Harthi; Abdullah Alqayoudhi; Abdullah Al Manji; Bader Al Rawahi; Seif Al-Abri
Journal:  Front Public Health       Date:  2021-12-09
  5 in total

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