Hidden Markov Models for Sepsis Detection in Preterm Infants

Antoine Honoré; Dong Liu; David Forsberg; Karen Coste; Eric Herlenius; Saikat Chatterjee; Mikael Skoglund

ICASSP 2020accepted0 citations

Hidden Markov Models for Sepsis Detection in Preterm Infants

Antoine Honoré, Dong Liu, David Forsberg, Karen Coste, Eric Herlenius, Saikat Chatterjee, Mikael Skoglund

Abstract

We explore the use of traditional and contemporary hidden Markov models (HMMs) for sequential physiological data analysis and sepsis prediction in preterm infants. We investigate the use of classical Gaussian mixture model based HMM, and a recently proposed neural network based HMM. To improve the neural network based HMM, we propose a discriminative training approach. Experimental results show the potential of HMMs over logistic regression, support vector machine and extreme learning machine.

BibTeX

@inproceedings{icassp2020_hiddenmarkovmode,
  title = {Hidden Markov Models for Sepsis Detection in Preterm Infants},
  author = {Antoine Honoré and Dong Liu and David Forsberg and Karen Coste and Eric Herlenius and Saikat Chatterjee and Mikael Skoglund},
  booktitle = {ICASSP 2020},
  year = {2020}
}