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Pregnancy

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Transformer-Based Wavelet-Scalogram Deep Learning for Improved Seizure Pattern Recognition in Post-Hypoxic-Ischemic Fetal Sheep EEG.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Hypoxic-ischemic (HI) events in newborns can trigger seizures, which are highly associated with later neurodevelopmental impairment. The precise detection of these seizures is a complex task requiring considerable very specialized expertise, undersco...

Exploring Random Forest Machine Learning for Fetal Movement Detection using Abdominal Acceleration and Angular Rate Data.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Fetal movement is a commonly monitored indicator of fetal wellbeing with reductions in fetal movement being associated with poor perinatal outcomes. However, more informative datasets of fetal movement are required for improved clinical decision maki...

Application of the random forest algorithm to predict skilled birth attendance and identify determinants among reproductive-age women in 27 Sub-Saharan African countries; machine learning analysis.

BMC public health
INTRODUCTION: Maternal mortality refers to a mother's death owing to complications arising from childbirth or pregnancy. This issue is a forefront public health challenge around the globe which is pronounced in low- and middle-income countries, parti...

Development and validation of a machine learning model for predicting intrapartum fever using pre-labor analgesia clinical indicators: a multicenter retrospective study.

BMC pregnancy and childbirth
BACKGROUND: Labor anesthesia is commonly used for pain relief during labor, but it can increase the risk of intrapartum fever. Currently, there are no reliable tools to predict which parturients might develop fever before labor anesthesia. The predic...

Proposing a machine learning-based model for predicting nonreassuring fetal heart.

Scientific reports
The capacity to forecast nonreassuring fetal heart (NFH) is essential for minimizing perinatal complications; therefore, this research aims to establish if a machine learning (ML) model can predict NFH. This was a retrospective analysis of informatio...

Reliability and validity of a novel single-lead portable electrocardiogram device for pregnant women: a comparative study.

BMC medical informatics and decision making
BACKGROUND: WenXinWuYang, a novel portable Artificial Intelligence Electrocardiogram (AI-ECG) device, can detect many kinds of abnormal heart disease and perform a single-lead ECG, but its reliability and validity among pregnant women is unclear. The...

Detection of obstetric anal sphincter injuries using machine learning-assisted impedance spectroscopy: a prospective, comparative, multicentre clinical study.

Scientific reports
To evaluate the clinical performance and safety of the ONIRY system for obstetric anal sphincter injuries (OASI) detection versus three-dimensional endoanal ultrasound (EAUS). A prospective, comparative, multicentre, international study. Poland, Czec...

Accuracy of machine learning and traditional statistical models in the prediction of postpartum haemorrhage: a systematic review.

BMJ open
OBJECTIVES: To evaluate whether postpartum haemorrhage (PPH) can be predicted using both machine learning (ML) and traditional statistical models.

Navigating Quality and Innovation: Actor-Network Theory and Hybrid Assemblages in Midwifery Practice, Implications of Maternity Early Warning Tools and Artificial Intelligence.

Nursing inquiry
Midwifery philosophy views childbearing as primarily normal, indicative of a woman's overall health. Midwifery practice focuses on supporting the human-to-human relationship between the midwife and the woman holding primacy. Despite the traditional f...

TCGAN: Temporal Convolutional Generative Adversarial Network for Fetal ECG Extraction Using Single-Channel Abdominal ECG.

IEEE journal of biomedical and health informatics
Noninvasive fetal ECG (FECG) monitoring holds significant importance in ensuring the normal development of the fetus. Since FECG is usually submerged by maternal ECG (MECG) and background noise in abdominal ECG (AECG), it is challenging to exactly re...