SODA-RL learns diverse treatment options for hypotension from data.
arXiv research
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Determining whether hypotensive patients in intensive care units (ICUs) should receive fluid bolus therapy (FBT) has been an extremely challenging task for intensive care physicians as the corresponding increase in blood pressure has been hard to predict. Our study utilized regression models and attention-based recurre…
Timely prediction of clinically critical events in Intensive Care Unit (ICU) is important for improving care and survival rate. Most of the existing approaches are based on the application of various classification methods on explicitly extracted statistical features from vital signals. In this work, we propose to elim…
A new CA-GAN architecture improves minority class data generation in health datasets.
Method uses semi-supervised learning to estimate optimal treatment regimes from medical records.
Bayesian method estimates dynamics from near-optimal trajectories.
PHASE predicts surgical complications from physiological signals.