Autor: |
Umar Ibrahim, Abdullahi, Pwavodi, Pwadubashiyi Coston, Ozsoz, Mehmet, Al-Turjman, Fadi, Galaya, Tirah, Agbo, Joy Johnson |
Předmět: |
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Zdroj: |
Journal of Experimental & Theoretical Artificial Intelligence; May2023, Vol. 35 Issue 4, p489-505, 17p |
Abstrakt: |
Coronaviridae family consists of many virulent viruses with zoonotic properties that can be transmitted from animals to humans. Different strains of these viruses have caused pandemic in the past such as Severe Respiratory Syndrome Coronavirus (SARS-CoV) in 2002, Middle East respiratory syndrome coronavirus (MERS-CoV) in 2012 and recently Severe Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) also known as COVID-19 in December 2019. Scientists utilised different approaches for the detection and characterisation of CoVs using samples such as serum, throat swabs, nose swabs, nasopharyngeal aspirates and bronchoalveolar lavages. The two common approaches include antigen-based approach and molecular diagnostic approach, which are hindered by limitations such as low sensitivity and requirement for high level of biosafety during isolation of the virus from cell culture. Thus, there is a need for developing a more rapid, sensitive, simple and cheap diagnostic kit for diagnosis of different strains of coronavirus. In this article, we overview 2019 novel coronavirus, pandemic, prior epidemics, diagnosis, treatments, identification of drugs detection based on classification and prediction using artificial intelligence-driven tools. We also overview in-lab molecular testing and on-site testing using CRISPR-based biosensing tools. We also outline limitations of laboratory techniques and open-research issues in the current state of CRISPR-based biosensing applications and artificial intelligence for treatment of Coronaviruses. [ABSTRACT FROM AUTHOR] |
Databáze: |
Complementary Index |
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