KRISHI
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Please use this identifier to cite or link to this item:
http://krishi.icar.gov.in/jspui/handle/123456789/76835
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Santhosh Kusappa | en_US |
dc.contributor.author | Ajitha Santhakumari | en_US |
dc.contributor.author | Sushma Pradeep | en_US |
dc.contributor.author | Kuralyanapalya Putta Honnappa Suresh | en_US |
dc.contributor.author | Sharanagouda S. Patil | en_US |
dc.contributor.author | Shiva Prasad Kollur | en_US |
dc.contributor.author | Chandan Shivmallu | en_US |
dc.date.accessioned | 2023-04-12T07:26:22Z | - |
dc.date.available | 2023-04-12T07:26:22Z | - |
dc.date.issued | 2022-12-16 | - |
dc.identifier.citation | K, Santhosh; S, Ajitha; Pradeep, Sushma; Honnappa Suresh, Kuralyanapalya Putta; Patil, Sharanagouda S; Kollur, Shiva Prasad; and Shivmallu, Chandan (2022) "Artificial intelligence and Machine Learning based Techniques in Analyzing the COVID-19 Gene Expression data: A Review," International Journal of Health and Allied Sciences: Vol. 11: Iss. 1, Article 12 | en_US |
dc.identifier.issn | 2278-4292 | - |
dc.identifier.uri | http://krishi.icar.gov.in/jspui/handle/123456789/76835 | - |
dc.description | Not Available | en_US |
dc.description.abstract | The novel Coronavirus associated with respiratory illness has become a new threat to human health as it is spreading very rapidly among the human population. Scientists and healthcare specialists throughout the world are still looking for a breakthrough technology to help combat the Covid-19 outbreak, despite the recent worldwide urgency. The use of Machine Learning (ML) and Artificial Intelligence (AI) in earlier epidemics has encouraged researchers by providing a fresh approach to combating the latest Coronavirus pandemic. This paper aims to comprehensively review the role of AI and ML for analysis of gene expressed data of COVID-19 | en_US |
dc.description.sponsorship | Not Available | en_US |
dc.language.iso | English | en_US |
dc.publisher | JSS University, Mysore | en_US |
dc.relation.ispartofseries | Not Available; | - |
dc.subject | Coronavirus | en_US |
dc.subject | Repurposing | en_US |
dc.subject | COVID-19 | en_US |
dc.subject | Machine learning | en_US |
dc.subject | Artificial intelligence | en_US |
dc.title | Artificial Intelligence and Machine Learning Based Techniques in Analyzing the COVID-19 Gene Expression Data: A Review | en_US |
dc.title.alternative | Not Available | en_US |
dc.type | Research Paper | en_US |
dc.publication.projectcode | Not Available | en_US |
dc.publication.journalname | The International Journal of Health & Allied Sciences | en_US |
dc.publication.volumeno | 11 | en_US |
dc.publication.pagenumber | 83-89 | en_US |
dc.publication.divisionUnit | Not Available | en_US |
dc.publication.sourceUrl | 10.55691/2278-344X.1013 | en_US |
dc.publication.authorAffiliation | Department of Computer Science, JSS College for Women, Mysore, India | en_US |
dc.publication.authorAffiliation | Department of Master of Computer Applications, Ramaiah Institute of Technology, Bangalore, India | en_US |
dc.publication.authorAffiliation | d ICAR National Institute of Veterinary Epidemiology and Disease Informatics (NIVEDI), Bengaluru, | en_US |
dc.publication.authorAffiliation | School of Physical Sciences, Amrita Vishwa Vidyapeetham, Mysuru Campus, Mysuru, India | en_US |
dc.ICARdataUseLicence | http://krishi.icar.gov.in/PDF/ICAR_Data_Use_Licence.pdf | en_US |
dc.publication.journaltype | Peer reviewed Journal | en_US |
dc.publication.naasrating | Not listed in the NAAS Journal List | en_US |
dc.publication.impactfactor | Not listed in Journal Impact factor list | en_US |
Appears in Collections: | AS-NIVEDI-Publication |
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