A new multimodal representation learning framework explicitly uses informative missingness patterns in structured and textual clinical data via Bayesian filtering to improve treatment policy learning and mortality prediction on sepsis ICU datasets.
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Learning Dynamic Representations and Policies from Multimodal Clinical Time-Series with Informative Missingness
A new multimodal representation learning framework explicitly uses informative missingness patterns in structured and textual clinical data via Bayesian filtering to improve treatment policy learning and mortality prediction on sepsis ICU datasets.