DeepAI AI Chat
Log In Sign Up

Early prediction of respiratory failure in the intensive care unit

by   Matthias Hüser, et al.

The development of respiratory failure is common among patients in intensive care units (ICU). Large data quantities from ICU patient monitoring systems make timely and comprehensive analysis by clinicians difficult but are ideal for automatic processing by machine learning algorithms. Early prediction of respiratory system failure could alert clinicians to patients at risk of respiratory failure and allow for early patient reassessment and treatment adjustment. We propose an early warning system that predicts moderate/severe respiratory failure up to 8 hours in advance. Our system was trained on HiRID-II, a data-set containing more than 60,000 admissions to a tertiary care ICU. An alarm is typically triggered several hours before the beginning of respiratory failure. Our system outperforms a clinical baseline mimicking traditional clinical decision-making based on pulse-oximetric oxygen saturation and the fraction of inspired oxygen. To provide model introspection and diagnostics, we developed an easy-to-use web browser-based system to explore model input data and predictions visually.


page 3

page 13


Machine learning for early prediction of circulatory failure in the intensive care unit

Intensive care clinicians are presented with large quantities of patient...

Early ICU Mortality Prediction and Survival Analysis for Respiratory Failure

Respiratory failure is the one of major causes of death in critical care...

NPRL: Nightly Profile Representation Learning for Early Sepsis Onset Prediction in ICU Trauma Patients

Sepsis is a syndrome that develops in response to the presence of infect...

Multi-Subset Approach to Early Sepsis Prediction

Sepsis is a life-threatening organ malfunction caused by the host's inab...

Computable Phenotypes to Characterize Changing Patient Brain Dysfunction in the Intensive Care Unit

In the United States, more than 5 million patients are admitted annually...

Benefit-aware Early Prediction of Health Outcomes on Multivariate EEG Time Series

Given a cardiac-arrest patient being monitored in the ICU (intensive car...

Predicting sepsis in multi-site, multi-national intensive care cohorts using deep learning

Despite decades of clinical research, sepsis remains a global public hea...