  A ventilator simulation system can make mechanical ventilation easier and
more effective. As a result, predicting a patient's ventilator pressure is
essential when designing a simulation ventilator. We suggested a hybrid deep
learning-based approach to forecast required ventilator pressure for patients.
This system is made up of Bi-LSTM and Bi-GRU networks. The SELU activation
function was used in our proposed model. MAE and MSE were used to examine the
accuracy of the proposed model so that our proposed methodology can be applied
to real-world problems. The model performed well against test data and created
far too few losses. Major parts of our research were data collection, data
analysis, data cleaning, building hybrid Bi-LSTM and Bi-GRU model, training the
model, model evaluation, and result analysis. We compared the results of our
research with some contemporary works, and our proposed model performed better
than those models.
