Table 1.

Applications of modern technology during COVID-19 pandemic.

S. No	Application	Description	References	Status in India
1	Diagnosis using radiology images	•AI is used to extract radiological features for timely and accurate COVID-19 diagnosis	Wang et al. [7], Narin [8], Wang et al. [10], XU et al. [12]	Yes [49,51,53]
		•Early detection of COVID-19 cases using different CNN models can be tested by increasing the number of images
		•COVID-Net, a deep CNN design can be used for detection of COVID-19 cases from CT images and X rays.
		•COVID-19 detection neural network (COVNet) detects COVID-19 and distinguish it from community acquired Pneumonia and other lung diseases.
		•3-dimensional deep learning model can be used for early detection of the COVID-19 Cases
2	Disease tracking	•Abnormal respiratory patterns classifier may contribute to large-scale screening of people infected with COVID-19	Wang et al. [19],	Yes [46]
		•Time-dependent SIR model is used to estimate the infected persons.
		•GRU neural network with bidirectional and attentional mechanisms (BI-AT-GRU) for classifying respiratory patterns.
		•SEIR - Susceptible, Exposed, Infectious, and Removed or Recovered model is used to forecast the trajectory of the outbreak.
3	Prediction outcome of patient’s health condition	•Supervised XGBoost classifier provides a simple and intuitive clinical test to precisely and quickly quantify the risk of death.	Yan, Zhang, Goncalves et al. [27], Qi et al. [29]	No [46]
		•he machine learning-based CT radiomics models showed feasibility and accuracy for predicting hospital stay in COVID-19 patients
4	Computational Biology and Medicines perspective	•BenevolentAI used to search for baricitinib, which is predicted to reduce the ability of the virus to infect lung cells.	Richardson et al. [31]	No [50]
5	Protein structure predictions	•Critical Assessment of Techniques for Protein Structure Prediction (CASP) using deep neural networks predict properties of the protein from its genetic sequence.	Jumper, Hassabis and Kholi [33], Yu and Koltun [34], He at al. [35]	Yes [52]
		•Convolutional network architectures is examined for dense prediction.
		•Residual learning framework is used to ease the training of networks that are substantially deeper for image recognition.
6	Drug discovery	•Integrated AI-based drug discovery pipeline to generate novel drug compounds.	Zhavoronkov et al. [37], Makhzani at al. [38]	Yes [48,54]
		•Adversarial autoencoders is used to disentangle the style and content of images, unsupervised clustering, dimensionality reduction and data visualization.
7	Awareness and social control through Internet	•Smartphone thermometer as an authentic and alternative apparatus for assessing temperature of infected people.	Maddah and Beigzadeh [41], Nemati et al. [42]	Yes [47]
		•Cough type detection using an extensive set of acoustic features applied to the recorded audio from a relatively large population of both healthy subjects and patient