Abstract
| Original language | English |
|---|---|
| Title of host publication | Computer-Based Medical Systems (CBMS), 2015 IEEE 28th International Symposium on |
| Publisher | Institute of Electrical and Electronics Engineers (IEEE) |
| Pages | 250-255 |
| Number of pages | 6 |
| DOIs | |
| Publication status | Published - Jun 2015 |
| Event | 2015 IEEE 28th International Symposium on Computer-Based Medical Systems (CBMS) - São Carlos and Ribeirão Preto, Brazil Duration: 22 Jun 2015 → 25 Jun 2015 |
Conference
| Conference | 2015 IEEE 28th International Symposium on Computer-Based Medical Systems (CBMS) |
|---|---|
| Country | Brazil |
| City | São Carlos and Ribeirão Preto |
| Period | 22/06/2015 → 25/06/2015 |
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Discrete Conditional Phase-type Model Utilising a Multiclass Support Vector Machine for the Prediction of Retinopathy of Prematurity. / Rollins, Rebecca; Marshall, Adele H.; McLoone, Eibhlin; Chamney, Sarah.
Computer-Based Medical Systems (CBMS), 2015 IEEE 28th International Symposium on. Institute of Electrical and Electronics Engineers (IEEE), 2015. p. 250-255.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
TY - GEN
T1 - Discrete Conditional Phase-type Model Utilising a Multiclass Support Vector Machine for the Prediction of Retinopathy of Prematurity
AU - Rollins, Rebecca
AU - Marshall, Adele H.
AU - McLoone, Eibhlin
AU - Chamney, Sarah
PY - 2015/6
Y1 - 2015/6
N2 - Retinopathy of prematurity (ROP) is a rare disease in which retinal blood vessels of premature infants fail to develop normally, and is one of the major causes of childhood blindness throughout the world. The Discrete Conditional Phase-type (DC-Ph) model consists of two components, the conditional component measuring the inter-relationships between covariates and the survival component which models the survival distribution using a Coxian phase-type distribution. This paper expands the DC-Ph models by introducing a support vector machine (SVM), in the role of the conditional component. The SVM is capable of classifying multiple outcomes and is used to identify the infant's risk of developing ROP. Class imbalance makes predicting rare events difficult. A new class decomposition technique, which deals with the problem of multiclass imbalance, is introduced. Based on the SVM classification, the length of stay in the neonatal ward is modelled using a 5, 8 or 9 phase Coxian distribution.
AB - Retinopathy of prematurity (ROP) is a rare disease in which retinal blood vessels of premature infants fail to develop normally, and is one of the major causes of childhood blindness throughout the world. The Discrete Conditional Phase-type (DC-Ph) model consists of two components, the conditional component measuring the inter-relationships between covariates and the survival component which models the survival distribution using a Coxian phase-type distribution. This paper expands the DC-Ph models by introducing a support vector machine (SVM), in the role of the conditional component. The SVM is capable of classifying multiple outcomes and is used to identify the infant's risk of developing ROP. Class imbalance makes predicting rare events difficult. A new class decomposition technique, which deals with the problem of multiclass imbalance, is introduced. Based on the SVM classification, the length of stay in the neonatal ward is modelled using a 5, 8 or 9 phase Coxian distribution.
U2 - 10.1109/CBMS.2015.78
DO - 10.1109/CBMS.2015.78
M3 - Conference contribution
SP - 250
EP - 255
BT - Computer-Based Medical Systems (CBMS), 2015 IEEE 28th International Symposium on
PB - Institute of Electrical and Electronics Engineers (IEEE)
ER -