Abstract
Recently, there has been an increase in preterm newborn's survival and as a result longer length of stay (LOS) in neonatal intensive care units (NICU) have been observed. Conseqyently, there has been an increased interest in accurate prediction of the LOS. Most of the existing techniques are based on physiological parameters i.e., scores such as (SNAP-II or SNAPPE-II). In this paper we propose to predict the length of stay using heart-rate measurements combined with physiological scores. We propose to model the heart-rate using Markov chain model and estimate transition probabilities using maximum likelihood estimator and the patient population from Neonatal Intensive Care Unit at McMaster Hospital. We then derive the maximum likelihood estimators of LOS using physiological measurements and transition probabilities. Training and test data sets were used to verify the proposed linear and nonlinear estimators.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08 |
| Pages | 2912-2915 |
| Number of pages | 4 |
| Publication status | Published - 2008 |
| Event | International Conference of the IEEE Engineering in Medicine and Biology Society 2008 - Vancouver Convention and Exhibition Centre, Vancouver, Canada Duration: 20 Aug 2008 → 25 Aug 2008 Conference number: 30th |
Conference
| Conference | International Conference of the IEEE Engineering in Medicine and Biology Society 2008 |
|---|---|
| Abbreviated title | EMBC 2008 |
| Country | Canada |
| City | Vancouver |
| Period | 20/08/08 → 25/08/08 |
Keywords
- Lengthof-stay prediction
- Markov chains
- Neonatal intensive care
Cite this
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Predicting the length of stay for neonates using heart-rate Markov models. / Jeremic, Aleksandar; Tan, Kenneth.
Proceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08. 2008. p. 2912-2915 4649812.Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review
TY - GEN
T1 - Predicting the length of stay for neonates using heart-rate Markov models
AU - Jeremic, Aleksandar
AU - Tan, Kenneth
PY - 2008
Y1 - 2008
N2 - Recently, there has been an increase in preterm newborn's survival and as a result longer length of stay (LOS) in neonatal intensive care units (NICU) have been observed. Conseqyently, there has been an increased interest in accurate prediction of the LOS. Most of the existing techniques are based on physiological parameters i.e., scores such as (SNAP-II or SNAPPE-II). In this paper we propose to predict the length of stay using heart-rate measurements combined with physiological scores. We propose to model the heart-rate using Markov chain model and estimate transition probabilities using maximum likelihood estimator and the patient population from Neonatal Intensive Care Unit at McMaster Hospital. We then derive the maximum likelihood estimators of LOS using physiological measurements and transition probabilities. Training and test data sets were used to verify the proposed linear and nonlinear estimators.
AB - Recently, there has been an increase in preterm newborn's survival and as a result longer length of stay (LOS) in neonatal intensive care units (NICU) have been observed. Conseqyently, there has been an increased interest in accurate prediction of the LOS. Most of the existing techniques are based on physiological parameters i.e., scores such as (SNAP-II or SNAPPE-II). In this paper we propose to predict the length of stay using heart-rate measurements combined with physiological scores. We propose to model the heart-rate using Markov chain model and estimate transition probabilities using maximum likelihood estimator and the patient population from Neonatal Intensive Care Unit at McMaster Hospital. We then derive the maximum likelihood estimators of LOS using physiological measurements and transition probabilities. Training and test data sets were used to verify the proposed linear and nonlinear estimators.
KW - Lengthof-stay prediction
KW - Markov chains
KW - Neonatal intensive care
UR - http://www.scopus.com/inward/record.url?scp=61849085867&partnerID=8YFLogxK
M3 - Conference Paper
C2 - 19163315
AN - SCOPUS:61849085867
SN - 9781424418152
SP - 2912
EP - 2915
BT - Proceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS'08
ER -