In:
Scientific Programming, Hindawi Limited, Vol. 2020 ( 2020-09-15), p. 1-13
Abstract:
Sepsis is a leading cause of mortality in intensive care units and costs hospitals billions of dollars annually worldwide. Predicting survival time for sepsis patients is a time-critical prediction problem. Considering the useful sequential information for sepsis development, this paper proposes a time-critical topic model (TiCTM) inspired by the latent Dirichlet allocation (LDA) model. The proposed TiCTM approach takes into account the time dependency structure between notes, measurement, and survival time of a sepsis patient. Experimental results on the public MIMIC-III database show that, overall, our method outperforms the conventional LDA and linear regression model in terms of recall, precision, accuracy, and F1-measure. It is also found that our method achieves the best performance by using 5 topics when predicting the probability for 30-day survival time.
Type of Medium:
Online Resource
ISSN:
1058-9244
,
1875-919X
DOI:
10.1155/2020/8884539
Language:
English
Publisher:
Hindawi Limited
Publication Date:
2020
detail.hit.zdb_id:
2070004-0
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