The Role of Artificial Intelligence and Machine Learning Techniques: Race for COVID-19 Vaccine

被引:27
作者
Kannan, Shantani [1 ]
Subbaram, Kannan [2 ]
Ali, Sheeza [2 ]
Kannan, Hemalatha [3 ]
机构
[1] Kumaraguru Coll Technol, Dept Elect & Commun Engn, Coimbatore, Tamil Nadu, India
[2] Maldives Natl Univ, Sch Med, Male, Maldives
[3] Jimma Univ, Dept Lab Sci & Pathol, Jimma, Ethiopia
来源
ARCHIVES OF CLINICAL INFECTIOUS DISEASES | 2020年 / 15卷 / 02期
关键词
Artificial Intelligence; Neural Networks; Machine Learning; Algorithms; Spike Glycoprotein; Deep Learning; NEURAL-NETWORKS; SWISS-MODEL; CORONAVIRUS; BIOLOGY;
D O I
10.5812/archcid.103232
中图分类号
R51 [传染病];
学科分类号
100401 ;
摘要
Context: In the healthcare system, Artificial Intelligence (AI) is emerging as a productive tool. There are instances where AI has done marvels in the diagnosis of various health conditions and the interpretation of complex medical disorders. Although AI is far from human intelligence, it can be used as an effective tool to study the SARS-CoV-2 and its capabilities, virulence, and genome. The progress of the pandemic can be tracked, and the patients can be monitored, thereby speeding up the research for the treatment of COVID-19. In this review article, we highlighted the importance of AI and Machine learning (ML) techniques that can speed up the path to the discovery of a possible cure for COVID-19. We also deal with the interactions between viromics and AI, which can hopefully find a solution to this pandemic. Evidence Acquisition: A review of different articles was conducted using the following databases: MEDLINE/PubMed, SCOPUS, Web of Science, ScienceDirect, and Google Scholar for recent studies regarding the use of AI, seeking the spread of different infectious diseases using relevant MeSH subheadings. Results: After a thorough screening of different articles, 30 articles were considered, and key information was obtained from them. Finally, the scope was broadened to obtain more information. Our findings indicated that AI/ML is a promising approach to drug development. Conclusions: The field of AI has enormous potential to predict the changes that may take place in the environment. If this technology is applied to situations of a pandemic such as COVID-19, breakthroughs could potentially pave the way for new vaccines and antiviral drugs.
引用
收藏
页数:9
相关论文
共 46 条
[1]   Predicting the sequence specificities of DNA- and RNA-binding proteins by deep learning [J].
Alipanahi, Babak ;
Delong, Andrew ;
Weirauch, Matthew T. ;
Frey, Brendan J. .
NATURE BIOTECHNOLOGY, 2015, 33 (08) :831-+
[2]   Deep Machine Learning-A New Frontier in Artificial Intelligence Research [J].
Arel, Itamar ;
Rose, Derek C. ;
Karnowski, Thomas P. .
IEEE COMPUTATIONAL INTELLIGENCE MAGAZINE, 2010, 5 (04) :13-18
[3]   Artificial neural networks: fundamentals, computing, design, and application [J].
Basheer, IA ;
Hajmeer, M .
JOURNAL OF MICROBIOLOGICAL METHODS, 2000, 43 (01) :3-31
[4]   GenBank [J].
Benson, Dennis A. ;
Clark, Karen ;
Karsch-Mizrachi, Ilene ;
Lipman, David J. ;
Ostell, James ;
Sayers, Eric W. .
NUCLEIC ACIDS RESEARCH, 2014, 42 (D1) :D32-D37
[5]   The SWISS-MODEL Repository-new features and functionality [J].
Bienert, Stefan ;
Waterhouse, Andrew ;
de Beer, Tjaart A. P. ;
Tauriello, Gerardo ;
Studer, Gabriel ;
Bordoli, Lorenza ;
Schwede, Torsten .
NUCLEIC ACIDS RESEARCH, 2017, 45 (D1) :D313-D319
[6]   Preparing for the future of Artificial Intelligence [J].
Alan Bundy .
AI & SOCIETY, 2017, 32 (2) :285-287
[7]  
Caterini AL, 2018, SPRINGERBRIEF COMPUT, P59, DOI 10.1007/978-3-319-75304-1_5
[8]   Biopython']python: freely available Python']Python tools for computational molecular biology and bioinformatics [J].
Cock, Peter J. A. ;
Antao, Tiago ;
Chang, Jeffrey T. ;
Chapman, Brad A. ;
Cox, Cymon J. ;
Dalke, Andrew ;
Friedberg, Iddo ;
Hamelryck, Thomas ;
Kauff, Frank ;
Wilczynski, Bartek ;
de Hoon, Michiel J. L. .
BIOINFORMATICS, 2009, 25 (11) :1422-1423
[9]  
Cohen JP, 2020, Covid-19 chest x-ray database
[10]   Machine learning meets genome assembly [J].
de Souza, Kleber Padovani ;
Setubal, Joao Carlos ;
de Carvalho, Andre Carlos Ponce de Leon F. ;
Oliveira, Guilherme ;
Chateau, Annie ;
Alves, Ronnie .
BRIEFINGS IN BIOINFORMATICS, 2019, 20 (06) :2116-2129