RAIM: Recurrent Attentive And Intensive Modeling Of Multimodal Continuous Patient Monitoring Data

Yanbo Xu Georgia Institute of Technology
Siddharth Biswal Georgia Institute of Technology
Shriprasad Deshpande Emory University School of Medicine
Kevin Maher Emory University School of Medicine
Jimeng Sun Georgia Institute of Technology


This paper studies the problem of modelling medical data.


With the improvement of medical data capturing, vast amount of continuous patient monitoring data, e.g., electrocardiogram (ECG), real-time vital signs and medications, become available for clinical decision support at intensive care units (ICUs). However, it becomes increasingly challenging to model such data, due to high density of the monitoring data, heterogeneous data types and the requirement for interpretable models.

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