Table 1.

Application areas of AI to combat COVID-19

AI and its implications in different area	Status/report of applications	References
Diagnosis and treatment	The AI-based testing procedure mainly focuses on medical imaging such as X-ray and computed tomography (CT), radiology, and predictive analysis procedure. The deep learning models such as UNet, UNet + + , VB-Net are used for image segmentation, classification, and assessing the severity of the disease with high accuracy. AI4COVID-19 app helps in preliminary diagnosis using cough samples. Bluedot and InferVision are the medical AI-based enterprises, help in early detection of COVID-19	[24, 32, 48–50]
COVID-19 genome analysis	Genome sequencing of hCOV-19 is available via Global Initiative on Sharing All Influenza Data (GISAID) enabling rapid and open access to virus data	[49, 51, 52]
COVID-19 vaccine development	Using the Vaxign reverse vaccinology-machine learning platform, suitable vaccine candidates can be predicted and COVID-19 High Performance Computing (HPC) Consortium is engaged in providing advanced computing resources for such projects	[25]
Infection tracking	The abnormal respiration pattern classifier based on Respiratory Simulation Model can help in large scale screening and tracking of COVID-19 patients. The ML-based prediction model deployed using the FogBus framework can predict the growth and trend of the pandemic. HealthMap helps in tracking and monitoring COVID-19 spread by gathering data in daily basis	[28, 53]
Prediction of patient outcome	XGBoost based machine learning platform can predict the survival rate of highly critical COVID-19 patients. EpiRisk is another such tool used for prediction of infection	[29]
Computational biology and medicines perspective	Baricitinib is identified by Benevolent AI’s knowledge graph as a potential drug to combat COVID-19	[33]
Protein structure predictions	Google's AI platform DeepMind-based protein structure prediction tool AlphaFold has predicted and released the 3D structures of several understudied proteins of the CoV-2 as an open-source. Antivirals/vaccines can be designed to combat the forthcoming COVID-19 pandemic. DeepTracer, a DNN based software can predict protein structure of SARS-CoV-2	[37]
Drug discovery and digital health	Structure-based virtual screening for drug discovery and drug repurposing. Data mining, machine learning, high-level quantum mechanical (QM), quantum- mechanical/ molecular—mechanical (QM/MM), and quantitative structure–activity relationship (QSAR) techniques are useful to accelerate the drug discovery program. AI-based inclProject IDentif.AI and PolypharmDB helps in identifying drugs against COVID-19	[2, 32, 38] [20]
Awareness and social control through the Internet	AI-enabled social media (Facebook and Twitter) survey enables monitoring and forecasting the spread of COVID-19 and thus helps in better preparedness and control. The range of apps like Arogya Setu(India), CloseContact (China), HaMagen (Israel), Mawid (Saudi Arabia), Tabaud (Saudi Arabia), Tawakkalna (Saudi Arabia), Sehha (Saudi Arabia), TraceTogether (Singapore), Covid Safe(Australia), Immuni(Italy), COVID Symptom Study(UK), NHS COVID-19(UK), COVID Watch (USA) & PathCheck SafePlaces (USA) gives information about the vicinity of a corona positive patient, risk assessment, test reports, educational resources, personalized health services and vaccination information	[17, 42, 54]
Reducing the workload of the medical staffs	The COVID-19 related inquiries of the public are addressed by medical 'chatbots' like Zini and Clara from the Centre for Disease Control. CovNet is developed to extract visual features from a CT scan predicting the contamination. CRUZR robot assist in high exposure tasks at hospitals	[2, 44] [20]