One of the most consequential decisions in intensive care is also one of the most difficult to make: when to liberate a ...
Please provide your email address to receive an email when new articles are posted on . By training artificial intelligence, or AI, algorithms with electronic health record data, researchers ...
In a recent article published in Npj Digital Medicine, researchers utilized electrocardiogram (ECG) data from a large retrospective cohort to extract various heart rate variability (HRV) measures.
Machine learning prediction of clinical tumor lysis syndrome in critically ill patients with hematologic malignancies using laboratory trajectory features: A MIMIC-IV retrospective cohort study.
Johns Hopkins University researchers have developed machine-learning (ML) algorithms that can detect the early warning signs of delirium and predict which patients will be at high risk of delirium at ...