Modeling Temporal Dynamics in Irregular ICU Data Using MWTA-LSTM

Mamadou Ben Hamidou Cissoko, Vincent Castelain, Nicolas Lachiche

Abstract: Accurately modeling a patient’s illness and care processes is crucial in personalized predictive medicine due to their long-term temporal dependencies. However, electronic health records often contain episodic and irregularly timed data, posing a challenge for constructing personalized predictive models.

External IDs:dblp:conf/epia/CissokoCL24