Towards Foundation Models for Critical Care Time Series

Understand

Notable progress has been made in generalist medical large language models across various healthcare areas.

• However, large-scale modeling of in-hospital time series data - such as vital signs, lab results, and treatments in critical care - remains underexplored.
• Existing datasets are relatively small, but combining them can enhance patient diversity and improve model robustness.
• To effectively utilize these combined datasets for large-scale modeling, it is essential to address the distribution shifts caused by varying treatment policies, necessitating the harmonization of treatment variables across the different datasets.