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Machine learning based classification in obstetrics: evaluating models, partitioning strategies, and key predictors

Radana Vilimkova Kahankova1, Katerina Barnova1,2, Ojan Majidzadeh Gorjani1

  • 1Department of Cybernetics and Biomedical Engineering, VSB - Technical University of Ostrava, 17. listopadu 2172/15, Ostrava, 708 00, Czechia.

BMC Pregnancy and Childbirth
|April 24, 2026
PubMed
Summary

No abstract available in PubMed .

Keywords:
CTG classificationImbalanced datasetMachine learningPredictor importanceSplit ratio

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Survival Tree01:19

Survival Tree

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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