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Related Experiment Video

Updated: Apr 19, 2026

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
12:18

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment

Published on: January 11, 2020

8.2K

Translating predictive models into clinical practice: fast-and-frugal trees for postoperative delirium using routine

Odette Wegwarth1,2, Felix Balzer3, Sebastian D Boie3

  • 1Department of Anesthesiology and Intensive Care Medicine | CCM | CVK, Heisenberg Chair for Medical Risk Literacy & Evidence-Based Decisions, Charité-Universitätsmedizin Berlin, 10117, Berlin, Germany. odette.wegwarth@charite.de.

Scientific Reports
|April 17, 2026
PubMed
Summary

No abstract available in PubMed .

Related Experiment Videos

Last Updated: Apr 19, 2026

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
12:18

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment

Published on: January 11, 2020

8.2K

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Survival Tree01:19

Survival Tree

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Survival trees are a non-parametric method used in survival analysis to model the relationship between a set of covariates and the time until an event of interest occurs, often referred to as the "time-to-event" or "survival time." This method is particularly useful when dealing with censored data, where the event has not occurred for some individuals by the end of the study period, or when the exact time of the event is unknown.
 Building a Survival Tree
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