SOURCE-LINKED INTELLIGENCE

Generative Pre-Training on MEDical event streams in Intensive Care

CORDIS · observation · Publication date unknown

Generative Pre-Training on MEDical event streams in Intensive Care Background: Artificial intelligence (AI) holds great promise for improving patient care, but challenges related to data irregularity and complexity have hindered its translation into clinical practice. Modelling rich longitudinal electronic health records (EHRs) such as those found in intensive care units (ICUs) remains especially difficult, as they represent a complex interplay between the patient’s health and clinical decisions made in response. Objectives: We aim to develop a robust AI framework for flexible prediction of any outcome in the ICU and beyond. We will pioneer a class of generative pre-trained models optimised for complex EHR data (Objective 1). Our approach will be rigorously benchmarked across outcomes and hospitals (Objective 2) on a secure, federated infrastructure that ensures data privacy (Objective 3). Methods: Our approach treats EHR data as a stream of clinical events in c

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recordType

award

status

SIGNED

region

EU

value

1491267

unit

EUR