DYNACARE: Dynamic Cardiac Arrest Risk Estimation

Abstract

Cardiac arrest is a deadly condition caused by a sudden failure of the heart with an in-hospital mortality rate of ∼80%. Therefore, the ability to accurately estimate patients at high risk of cardiac arrest is crucial for improving the survival rate. Existing research generally fails to utilize a patient’s temporal dynamics. In this paper, we present two dynamic cardiac risk estimation models, focusing on different temporal signatures in a patient’s risk trajectory. These models can track a patient’s risk trajectory in real time, allow interpretability and predictability of a cardiac arrest event, provide an intuitive visualization to medical professionals, offer a personalized dynamic hazard function, and estimate the risk for a new patient.

Cite

Text

Ho et al. "DYNACARE: Dynamic Cardiac Arrest Risk Estimation." International Conference on Artificial Intelligence and Statistics, 2013.

Markdown

[Ho et al. "DYNACARE: Dynamic Cardiac Arrest Risk Estimation." International Conference on Artificial Intelligence and Statistics, 2013.](https://mlanthology.org/aistats/2013/ho2013aistats-dynacare/)

BibTeX

@inproceedings{ho2013aistats-dynacare,
  title     = {{DYNACARE: Dynamic Cardiac Arrest Risk Estimation}},
  author    = {Ho, Joyce C. and Park, Yubin and Carvalho, Carlos and Ghosh, Joydeep},
  booktitle = {International Conference on Artificial Intelligence and Statistics},
  year      = {2013},
  pages     = {333-341},
  url       = {https://mlanthology.org/aistats/2013/ho2013aistats-dynacare/}
}