ArticleSensors (Basel, Switzerland)2020
Electrohysterogram for ANN-Based Prediction of Imminent Labor in Women with Threatened Preterm Labor Undergoing Tocolytic Therapy.
Article in Sensors (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed, 26 citations in OpenAlex.
- Analysis of electrohysterogram signals for predicting obstetric outcome using machine learning methods: a scoping review.BMC pregnancy and childbirth · 2026Article
- Deep learning model using continuous skin temperature data predicts labor onset.BMC pregnancy and childbirth · 2024Article
- Use of uterine electromyography in the prediction of preterm birth after transvaginal cervical cerclage.BMC pregnancy and childbirth · 2024Article
- Prediction of Preterm Labor from the Electrohysterogram Signals Based on Different Gestational Weeks.Sensors (Basel, Switzerland) · 2023Article
- Combination of Feature Selection and Resampling Methods to Predict Preterm Birth Based on Electrohysterographic Signals from Imbalance Data.Sensors (Basel, Switzerland) · 2022Article
- Oral nifedipine and parenteral isoxsuprine in arresting preterm labor: A comparative study.Journal of family medicine and primary care · 2022Article
- Assessment of Features between Multichannel Electrohysterogram for Differentiation of Labors.Sensors (Basel, Switzerland) · 2022Article
- Development and validation of a transcriptomic signature-based model as the predictive, preventive, and personalized medical strategy for preterm birth within 7 days in threatened preterm labor women.The EPMA journal · 2022Article
- Assessment of Dispersion and Bubble Entropy Measures for Enhancing Preterm Birth Prediction Based on Electrohysterographic Signals.Sensors (Basel, Switzerland) · 2021Article
- Optimized Feature Subset Selection Using Genetic Algorithm for Preterm Labor Prediction Based on Electrohysterography.Sensors (Basel, Switzerland) · 2021Article
- Optimization of Imminent Labor Prediction Systems in Women with Threatened Preterm Labor Based on Electrohysterography.Sensors (Basel, Switzerland) · 2021Article
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Authors and funding
8 authors at 1 institution in 1 country.
Funding
Abstract
Threatened preterm labor (TPL) is the most common cause of hospitalization in the second half of pregnancy and entails high costs for health systems. Currently, no reliable labor proximity prediction techniques are available for clinical use. Regular checks by uterine electrohysterogram (EHG) for predicting preterm labor have been widely studied. The aim of the present study was to assess the feasibility of predicting labor with a 7- and 14-day time horizon in TPL women, who may be under tocolytic treatment, using EHG and/or obstetric data. Based on 140 EHG recordings, artificial neural networks were used to develop prediction models. Non-linear EHG parameters were found to be more reliable than linear for differentiating labor in under and over 7/14 days. Using EHG and obstetric data, the <7- and <14-day labor prediction models achieved an AUC in the test group of 87.1 ± 4.3% and 76.2 ± 5.8%, respectively. These results suggest that EHG can be reliable for predicting imminent labor in TPL women, regardless of the tocolytic therapy stage. This paves the way for the development of diagnostic tools to help obstetricians make better decisions on treatments, hospital stays and admitting TPL women, and can therefore reduce costs and improve maternal and fetal wellbeing.
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