Artificial intelligence in COVID-19 drug repurposing

Zhou, Yadi; Wang, Fei; Tang, Jian; Nussinov, Ruth; Cheng, Feixiong

doi:10.1016/s2589-7500(20)30192-8

Cited by 430 publications

(324 citation statements)

References 73 publications

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“…Drug repurposing is a promising approach for the COVID-19 pandemic because of the speed and low cost required for development and approval [ 4 – 8 ]. Accumulating evidence suggests that SARS-CoV-2 infection has deleterious effects in the central nervous system (CNS), which can result in psychiatric and neurological symptoms in infected individuals [ 9 – 13 ].…”

Section: Introductionmentioning

confidence: 99%

Repurposing of CNS drugs to treat COVID-19 infection: targeting the sigma-1 receptor

Hashimoto

2021

Eur Arch Psychiatry Clin Neurosci

101

115

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Section: Introductionmentioning

confidence: 99%

Repurposing of CNS drugs to treat COVID-19 infection: targeting the sigma-1 receptor

Hashimoto

2021

Eur Arch Psychiatry Clin Neurosci

101

115

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“…[ 121 ] also look at combining a white blood cell test with CT images for diagnosis. Zhou et al [ 122 ] imagine the integration of genomic, transcriptomic, proteomic, and phenomic profiles for a more personalized treatment in drug repurposing. We will describe this application later on the survey.…”

Section: Deep Learning Applications For Covid-19mentioning

confidence: 99%

“…We will describe this application later on the survey. We refer readers to the illustrative diagram from their study [ 122 ] describing the integration of different data sources for Precision Diagnostics, shown in Fig. 14 .…”

Section: Deep Learning Applications For Covid-19mentioning

confidence: 99%

Deep Learning applications for COVID-19

2021

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This survey explores how Deep Learning has battled the COVID-19 pandemic and provides directions for future research on COVID-19. We cover Deep Learning applications in Natural Language Processing, Computer Vision, Life Sciences, and Epidemiology. We describe how each of these applications vary with the availability of big data and how learning tasks are constructed. We begin by evaluating the current state of Deep Learning and conclude with key limitations of Deep Learning for COVID-19 applications. These limitations include Interpretability, Generalization Metrics, Learning from Limited Labeled Data, and Data Privacy. Natural Language Processing applications include mining COVID-19 research for Information Retrieval and Question Answering, as well as Misinformation Detection, and Public Sentiment Analysis. Computer Vision applications cover Medical Image Analysis, Ambient Intelligence, and Vision-based Robotics. Within Life Sciences, our survey looks at how Deep Learning can be applied to Precision Diagnostics, Protein Structure Prediction, and Drug Repurposing. Deep Learning has additionally been utilized in Spread Forecasting for Epidemiology. Our literature review has found many examples of Deep Learning systems to fight COVID-19. We hope that this survey will help accelerate the use of Deep Learning for COVID-19 research.

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“…These models were then used to predict the transmission dynamics of COVID-19 and hence curb its spread [25]. Lastly AI has contributed extensively in new drug design and drug repurposing for COVID19 [26,27].…”

Section: Rapidity Of Artificial Intelligence In Diagnosismentioning

confidence: 99%

COVID-19 and Artificial Intelligence: the pandemic pacifier

Banerjee¹,

Robinson²,

Kashyap³

et al. 2020

Nepal J Epidemiology

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COVID-19 remains a threat to the entire world. In an attempt to curb its spread and facilitate its treatment, the technological tool that is Artificial Intelligence (AI) is being researched as a potential alternative to conventional methods. Industrial Revolution 4.0 marks the dawn to the combination of digital, physical and biological systems, by application of digital skills such as Blockchain, Internet of things, Artificial Intelligence and Big data. AI tools in SARS-COV-2 pandemic are highly competitive to human performance, such as rapid screening and diagnosis of the disease, surveilling the efficacy of the treatment, keeping record and depicting active cases and mortality, inventions of medications and vaccines, relieving the workload of healthcare workers and extinguishing the spread of the disease. Contact tracing platforms like Aarogya Setu App, implemented by the Government of India, Australian Government's COVID Safe app, Trace Together- a Bluetooth-based contact tracing app developed in Singapore; based on syndromic mapping/surveillance technology. Artificial intelligence will become a mainstay in both the diagnosis and treatment of COVID-19 as well as similar pandemics in future. The application and system development will be challenging; the accuracy and rapidity of its use far outweigh this drawback. The current global technological leaders have proven that the retro modification of current data systems and applications have been indispensable in the war on COVID-19, thus permanently securing their development and application in future.

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Artificial intelligence in COVID-19 drug repurposing

Cited by 430 publications

References 73 publications

Repurposing of CNS drugs to treat COVID-19 infection: targeting the sigma-1 receptor

Repurposing of CNS drugs to treat COVID-19 infection: targeting the sigma-1 receptor

Deep Learning applications for COVID-19

COVID-19 and Artificial Intelligence: the pandemic pacifier

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