ABSTRACT
Researchers have found many similarities between the 2003 severe acute respiratory syndrome (SARS) virus and SARS-CoV-19 through existing data that reveal the SARS's cause. Artificial intelligence (AI) learning models can be created to predict drug structures that can be used to treat COVID-19. Despite the effectively demonstrated repurposed drugs, more repurposed drugs should be recognized. Furthermore, technological advancements have been helpful in the battle against COVID-19. Machine intelligence technology can support this procedure by rapidly determining adequate and effective drugs against COVID-19 and by overcoming any barrier between a large number of repurposed drugs, laboratory/clinical testing, and final drug authorization. This paper reviews the proposed vaccines and medicines for SARS-CoV-2 and the current application of AI in drug repurposing for COVID-19 treatment.
Subject(s)
Artificial Intelligence , COVID-19 Drug Treatment , Drug Development , Drug Repositioning , Adenosine Monophosphate/analogs & derivatives , Adenosine Monophosphate/therapeutic use , Alanine/analogs & derivatives , Alanine/therapeutic use , Antibodies, Monoclonal, Humanized/therapeutic use , Antiviral Agents/therapeutic use , Ascorbic Acid/therapeutic use , COVID-19/prevention & control , COVID-19 Vaccines/therapeutic use , Chloroquine/therapeutic use , Deep Learning , Drug Combinations , Humans , Hydroxychloroquine/therapeutic use , Immunosuppressive Agents/therapeutic use , Lopinavir/therapeutic use , Machine Learning , Ribavirin/therapeutic use , Ritonavir/therapeutic use , Vitamins/therapeutic useABSTRACT
Recent Coronavirus (COVID-19) is one of the respiratory diseases, and it is known as fast infectious ability. This dissemination can be decelerated by diagnosing and quarantining patients with COVID-19 at early stages, thereby saving numerous lives. Reverse transcription-polymerase chain reaction (RT-PCR) is known as one of the primary diagnostic tools. However, RT-PCR tests are costly and time-consuming; it also requires specific materials, equipment, and instruments. Moreover, most countries are suffering from a lack of testing kits because of limitations on budget and techniques. Thus, this standard method is not suitable to meet the requirements of fast detection and tracking during the COVID-19 pandemic, which motived to employ deep learning (DL)/convolutional neural networks (CNNs) technology with X-ray and CT scans for efficient analysis and diagnostic. This study provides insight about the literature that discussed the deep learning technology and its various techniques that are recently developed to combat the dissemination of COVID-19 disease.
