A transformer-based diffusion probabilistic model for heart rate and blood pressure forecasting in Intensive Care Unit
Abstract: Highlights•The TDSTF model forecasts vital signs based on all events in the MIMIC-III dataset.•The proposed model captures temporal patterns in both slow and sudden changes.•The MSE of the model improves by 34.3% over the best baseline model.•The SACRPS of the model improves by 18.9% over the best baseline model.•The inference speed of the model is more than 17 times faster than the best baseline model.
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