Acute Brain Dysfunction

Acute brain dysfunction (ABD), encompassing conditions like delirium and coma, is a significant clinical challenge, particularly in intensive care units (ICUs), characterized by high prevalence and mortality. Current research focuses on developing automated prediction systems for ABD using electronic health records (EHR) data, employing machine learning models such as transformer networks and state-space models to analyze both static and temporal patient information and predict ABD states at fine-grained intervals (e.g., 12 hours). These advancements aim to improve early diagnosis, facilitate timely interventions, and ultimately optimize patient care and resource allocation within the ICU setting.