ABSTRACT
Coronavirus disease 2019 (COVID-19) is a major threat throughout the world. The latest advancements in the field of computational techniques based on Artificial Intelligence (AI), Machine Learning (ML) and Big Data can help in detecting, monitoring and forecasting the severity of the COVID-19 pandemic. We aim to review the detection of the COVID-19 pandemic empowered by AI, major implications, challenges and the future of smart health care at a glance. The AI plays a pioneering role in rapid and improved detection of the disease. It helps in modeling the disease activity and predicting the severity for better decision making and preparedness by healthcare authorities and policymakers. It is a promising technology for automatic and fully transparent monitoring system to track and treat the patients remotely without spreading the virus to others. The future application areas of AI-based healthcare are also identified. The role of AI in tackling the COVID-19 pandemic is reviewed in this paper. AI proves beneficial in early detection with improved results. It also provides solution for contact tracing, prediction, drug development thus reducing the workload of medical industry.
ABSTRACT
BACKGROUND AND AIM: COVID-19 outbreak has created havoc and a quick cure for the disease will be a therapeutic medicine that has usage history in patients to resolve the current pandemic. With technological advancements in Artificial Intelligence (AI) coupled with increased computational power, the AI-empowered drug repurposing can prove beneficial in the COVID-19 scenario. METHODS: The recent literature is studied and analyzed from various sources such as Scopus, Google Scholar, PubMed, and IEEE Xplore databases. The search terms used are 'COVID-19', ' AI ', and 'Drug Repurposing'. RESULTS: AI is implemented in the field design through the generation of the learning-prediction model and performs a quick virtual screening to accurately display the output. With a drug-repositioning strategy, AI can quickly detect drugs that can fight against emerging diseases such as COVID-19. This technology has the potential to improve the drug discovery, planning, treatment, and reported outcomes of the COVID-19 patient, being an evidence-based medical tool. CONCLUSIONS: Thus, there are chances that the application of the AI approach in drug discovery is feasible. With prior usage experiences in patients, few of the old drugs, if shown active against SARS-CoV-2, can be readily applied to treat the COVID-19 patients. With the collaboration of AI with pharmacology, the efficiency of drug repurposing can improve significantly.
Subject(s)
Artificial Intelligence , Betacoronavirus/drug effects , Coronavirus Infections/drug therapy , Drug Repositioning/methods , Pneumonia, Viral/drug therapy , COVID-19 , Coronavirus Infections/virology , Humans , Pandemics , Pneumonia, Viral/virology , SARS-CoV-2 , COVID-19 Drug TreatmentABSTRACT
BACKGROUND AND AIM: In the age of advanced digital technology, smart healthcare based on the Internet of Things (IoT) is gaining importance to deal with the current COVID-19 pandemic. In this paper, the novel application of cognitive radio (CR) based IoT specific for the medical domain referred to as Cognitive Internet of Medical Things (CIoMT) is explored to tackle the global challenge. This concept of CIoT is best suited to this pandemic as every person is to be connected and monitored through a massive network that requires efficient spectrum management. METHODS: An extensive literature survey is conducted in the Google Scholar, Scopus, PubMed, Research Gate, and IEEE Xplore databases using the terms "COVID-19" and "Cognitive IoT" or "Corona virus" and "IoMT". The latest data and inputs from official websites and reports are used for further investigation and analysis of the application areas. RESULTS: This review encompasses different novel applications of CIoMT for fighting the ongoing COVID-19 health crisis. The CR based dynamic spectrum allocation technique is the solution for accommodating a massive number of devices and a wide number of applications. The CIoMT platform enables real-time tracking, remote health monitoring, rapid diagnosis of the cases, contact tracking, clustering, screening, and surveillance thus, reducing the workload on the medical industry for prevention and control of the infection. The challenges and future research directions are also identified. CONCLUSIONS: CIoMT is a promising technology for rapid diagnosis, dynamic monitoring and tracking, better treatment and control without spreading the virus to others.