Abstract:
:The past 25 years have witnessed the development of improved tools with which to predict short-term and long-term outcomes after critical illness. The general paradigm for constructing the best known tools has been the logistic regression model. Recently, a variety of alternative tools, such as artificial neural networks, have been proposed, with claims of improved performance over more traditional models in particular settings. However, these newer methods have yet to demonstrate their practicality and usefulness within the context of predicting outcomes in the critically ill.
journal_name
Crit Carejournal_title
Critical care (London, England)authors
Clermont Gdoi
10.1186/cc3507keywords:
subject
Has Abstractpub_date
2005-04-01 00:00:00pages
153-4issue
2eissn
1364-8535issn
1466-609Xpii
cc3507journal_volume
9pub_type
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