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For all these reasons, the use of prognostic models for decision-making in individual cases carries many dangers.
However, a significant barrier to the widespread practical use of prognostic models is their perceived lack of clinical credibility [ 8].
The use of prognostic models, as proposed from this analysis, may be important for discussing patient entry into trials and could, in future, be helpful as part of the inclusion criteria.
The decision between surveillance and treatment remains a clinical one; however, use of prognostic models may help guide the decision between more aggressive therapy vs avoidance of therapy-related complications and preservation of quality of life.
In particular, spliceosome mutations, implying abnormalities of mRNA splicing in the pathogenesis of MDS, have variable prognostic relevance, depending on the mutated splicing factor 6– 9. From a practical point of view, the definition of individual risk requires the use of prognostic models.
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Using inductive methods of prognostic models based on temporal sequence discovery within the bootstrap procedure is however novel at least in predictive models in the Intensive Care.
It is also representative of the population in which such a model is likely to be used and has been used successfully to develop and validate a range of prognostic models for use in primary care 9 10 as well as models designed to help earlier detection of other cancers.
To investigate the behavior of predictive performance measures that are commonly used in external validation of prognostic models for outcome at intensive care units (ICUs).
Our study suggests that a standardised segmentation methodology should be used for the development of prognostic models.
Performance of prognostic models constructed using the lasso technique can be optimistic as well.
Standardised image features were calculated, and a series of prognostic models were developed using identical clinical data.
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