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Ensemble prediction...
Ensemble prediction of time-to-event outcomes with competing risks: a case-study of surgical complications in Crohn's disease
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- Sachs, MC (author)
- Karolinska Institutet
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- Discacciati, A (author)
- Karolinska Institutet
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- Everhov, AH (author)
- Karolinska Institutet
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- Olen, O (author)
- Karolinska Institutet
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- Gabriel, EE (author)
- Karolinska Institutet
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(creator_code:org_t)
- 2019-07-18
- 2019
- English.
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In: JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES C-APPLIED STATISTICS. - : Oxford University Press (OUP). - 0035-9254 .- 1467-9876. ; 68:5, s. 1431-1446
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Abstract
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- We develop a novel algorithm to predict the occurrence of major abdominal surgery within 5 years following Crohn's disease diagnosis by using a panel of 29 baseline covariates from the Swedish population registers. We model pseudo-observations based on the Aalen–Johansen estimator of the cause-specific cumulative incidence with an ensemble of modern machine learning approaches. Pseudo-observation preprocessing easily extends all existing or new machine learning procedures for continuous data to right-censored event history data. We propose pseudo-observation-based estimators for the area under the time varying receiver operating characteristic curve, for optimizing the ensemble, and the predictiveness curve, for evaluating and summarizing predictive performance.
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- vet (subject category)
- art (subject category)
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