Abstract
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.
Original language | English |
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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) |
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Country | Brazil |
City | São Carlos and Ribeirão Preto |
Period | 22/06/2015 → 25/06/2015 |