Optimized Feature Subset Selection Using Genetic Algorithm for Preterm Labor Prediction Based on Electrohysterography

Optimized Feature Subset Selection Using Genetic Algorithm for Preterm Labor Prediction Based on Electrohysterography

Electrohysterography (EHG) has emerged as an alternative technique to predict preterm labor, which still remains a challenge for the scientific-technical community. Based on EHG parameters, complex classification algorithms involving non-linear transformation of the input features, which clinicians...

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Bibliographic Details
Main Authors: Félix Nieto-del-Amor, Gema Prats-Boluda, Jose Luis Martinez-De-Juan, Alba Diaz-Martinez, Rogelio Monfort-Ortiz, Vicente Jose Diago-Almela, Yiyao Ye-Lin
Format: Article
Language:English
Published: MDPI AG 2021-05-01
Series:Sensors
Subjects:
preterm labor
electrohysterography
myoelectric activity
genetic algorithm
ensemble learning
Online Access:https://www.mdpi.com/1424-8220/21/10/3350

Internet

https://www.mdpi.com/1424-8220/21/10/3350

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