Combination of Feature Selection and Resampling Methods to Predict Preterm Birth Based on Electrohysterographic Signals from Imbalance Data

Research article (Sensors, 2022) · cited 21× · AI/ML
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Combination of Feature Selection and Resampling Methods to Predict Preterm Birth Based on Electrohysterographic Signals from Imbalance Data

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Combination of Feature Selection and Resampling Methods to Predict Preterm Birth Based on Electrohysterographic Signals from Imbalance Data is a scholarly article[1].

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APA 4ort.xyz Knowledge Graph. (2026). Combination of Feature Selection and Resampling Methods to Predict Preterm Birth Based on Electrohysterographic Signals from Imbalance Data. Retrieved May 24, 2026, from https://4ort.xyz/entity/combination-of-feature-selection-and-resampling-methods-to-predict-preterm-birth-based-on-electrohysterographic-signals-
MLA “Combination of Feature Selection and Resampling Methods to Predict Preterm Birth Based on Electrohysterographic Signals from Imbalance Data.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/combination-of-feature-selection-and-resampling-methods-to-predict-preterm-birth-based-on-electrohysterographic-signals-.
BibTeX @misc{4ortxyz_combination-of-feature-selection-and-resampling-methods-to-predict-preterm-birth-based-on-electrohysterographic-signals-_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Combination of Feature Selection and Resampling Methods to Predict Preterm Birth Based on Electrohysterographic Signals from Imbalance Data}}, year = {2026}, url = {https://4ort.xyz/entity/combination-of-feature-selection-and-resampling-methods-to-predict-preterm-birth-based-on-electrohysterographic-signals-}, note = {Accessed: 2026-05-24}}
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