ICU auxiliary intervention means prediction method based on deep learning

The invention discloses an ICU auxiliary intervention means prediction method based on deep learning, and belongs to the technical field of data processing, and the method comprises the steps: obtaining an MIMIC-III database, and extracting the EHR data of a patient in an intensive care unit; cleaning and processing the EHR data and then converting the EHR data into time sequence data; constructing a neural network model composed of a graph learning layer, an expansion causal convolution, an output module and a full connection layer, and training and updating the neural network model; time sequence data is used as input, a prediction judgment value is generated through the neural network model, and guidance is provided for intervention means. According to the method, a neural network model is constructed based on a deep learning algorithm, various clinical physiological indexes of a patient in an ICU are used as feature nodes of time sequence change, physiological information of the patient is used as feature