The early prediction of sepsis is potentially life-saving, and we challenge participants to predict sepsis 6 hours before the clinical prediction of sepsis.
Deep learning model for sepsis prediction using high-frequency data
Sepsis is a life-threatening condition with high mortality rates. Early detection and treatment are critical to improving outcomes
Sepsis occurs when chemicals released in the bloodstream to fight an infection trigger inflammation throughout the body. This can cause a cascade of changes that damage multiple organ systems, leading them to fail, sometimes even resulting in death.
In this project, we used eICU Collaborative Research Database. The eICU Collaborative Research Database is a large multi-center critical care database made available by Philips Healthcare in partnership with the MIT Laboratory for Computational Physiology.
- 1.Temporal Convolutional Neural Network