Prediction of Omicron cases in India using LSTM: An advanced approach of artificial intelligence

Abstract

Several mutants of SARS COV-2 have been reported so far, each one having different severity and infectivity rate. Omicron has enhanced resistance to host immunity and displays higher transmission. 15 of the 37 known mutations in the spike protein’s receptor-binding domain (RBD), the primary target of neutralising antibodies, are found there. An enhanced RNN, or sequential network, called a long short-term memory network, permits informatics data to endure. It is capable of resolving the RNN’s vanishing gradient issue. RNN, also referred to as a recurrent neural network, is utilized for persistent memory. “In medication, the right analysis and the perfect opportunity are the keys for effective treatment. For the current review, the gathered Past information was utilized to train the model, and afterward this trained model was utilized to test new information and afterward for utilized for the advancement of the prediction model”. The trained ML model’s presentation or approval was assessed utilizing some piece of accessible past datasets and this method known as validation process. According to findings of the current study, Indian citizens can aid their nation in the fight against Omicron by adhering to the directions and instructions provided by the Indian government. We ought to cooperate to overcome the new lethal variation of Coronavirus.