  We develop a deep learning approach to predicting a set of ventilator
parameters for a mechanically ventilated septic patient using a long and short
term memory (LSTM) recurrent neural network (RNN) model. We focus on short-term
predictions of a set of ventilator parameters for the septic patient in
emergency intensive care unit (EICU). The short-term predictability of the
model provides attending physicians with early warnings to make timely
adjustment to the treatment of the patient in the EICU. The patient specific
deep learning model can be trained on any given critically ill patient, making
it an intelligent aide for physicians to use in emergent medical situations.
