Can I read Hidden Markov Models for sepsis detection in preterm infants on EtoBox?

Hidden Markov Models for sepsis detection in preterm infants by Honore, Antoine; Liu, Dong; Forsberg, David; Coste, Karen; Herlenius, Eric; Chatterjee, Saikat; Skoglund, Mikael is a scholarly article available to read on EtoBox.

What is Hidden Markov Models for sepsis detection in preterm infants about?

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.

Author

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

Published

2019

Language

EN