Ensemble Deep Learning Approach with Attention Mechanism for COVID-19 Detection and Prediction

New coronavirus (COVID-19), which first appeared in Wuhan City and is now rapidly disseminating worldwide, may be predicted, diagnosed, and treated with the help of cutting-edge medical technology, such as artificial intelligence and machine learning algorithms. To detect COVID-19, we suggested an Ensemble deep learning method with an attention mechanism. The suggested approach uses an ensemble of RNN and CNN to extract features from data from diverse sources, such as CT scan pictures and blood test results. For image and video processing, CNNs are the most effective. RNNs, on the other hand, use text and speech data to extract features. Further, an attention mechanism is used to determine which features are most relevant for classification. Finally, the deep learning network utilizes the selected features for detection and prediction. As a result, data can be used to forecast future medical needs.