RETRACTED ARTICLE: Prediction of pre-term groups from EHG signals using optimal multi-kernel SVM

The preterm birth anticipation is a crucial task that can reduce the rate of preterm birth and also the complications of preterm birth. Electrohysterogram (EHG) or uterine electromyogram (EMG) data have been evidenced that they can provide an information useful for preterm birth anticipation. Four distinct time-domain features, i.e., mean absolute value, average amplitude change, difference absolute standard deviation value, and log detector, commonly applied to EMG signal processing are applied and investigated in this study. A single-channel of EHG data is decomposed into its constituent components, i.e., intrinsic mode functions, using empirical mode decomposition (EMD) before their time-domain features are extracted. The time-domain features of intrinsic mode functions of EHG data associated with preterm and term births are applied for preterm-term

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A comprehensive survey on the ant lion optimiser, variants and applications

Pathak

Gangwar

Singh

et al. 2022

Journal of Experimental & Theoretical Artificial Intelligen

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RETRACTED ARTICLE: Prediction of pre-term groups from EHG signals using optimal multi-kernel SVM

Cited by 4 publications

References 19 publications

An automated pre-term prediction system using EHG signal with the aid of deep learning technique

An automated pre-term prediction system using EHG signal with the aid of deep learning technique

Preterm-term birth classification using EMD-based time-domain features of single-channel electrohysterogram data

A comprehensive survey on the ant lion optimiser, variants and applications

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