AIMC Topic: Cardiotocography

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The Design and Implementation of Cardiotocography Signals Classification Algorithm Based on Neural Network.

Computational and mathematical methods in medicine
Mobile medical care is a hot issue in current medical research. Due to the inconvenience of going to hospital for fetal heart monitoring and the limited medical resources, real-time monitoring of fetal health on portable devices has become an urgent ...

Prognostic model based on image-based time-frequency features and genetic algorithm for fetal hypoxia assessment.

Computers in biology and medicine
Cardiotocography (CTG) is applied routinely for fetal monitoring during the perinatal period to decrease the rates of neonatal mortality and morbidity as well as unnecessary interventions. The analysis of CTG traces has become an indispensable part o...

Machine learning ensemble modelling to classify caesarean section and vaginal delivery types using Cardiotocography traces.

Computers in biology and medicine
Human visual inspection of Cardiotocography traces is used to monitor the foetus during labour and avoid neonatal mortality and morbidity. The problem, however, is that visual interpretation of Cardiotocography traces is subject to high inter and int...

Classification of caesarean section and normal vaginal deliveries using foetal heart rate signals and advanced machine learning algorithms.

Biomedical engineering online
BACKGROUND: Visual inspection of cardiotocography traces by obstetricians and midwives is the gold standard for monitoring the wellbeing of the foetus during antenatal care. However, inter- and intra-observer variability is high with only a 30% posit...

Combining latent class analysis labeling with multiclass approach for fetal heart rate categorization.

Physiological measurement
The most common approach to assess fetal well-being during delivery is monitoring of fetal heart rate and uterine contractions-the cardiotocogram (CTG). Nevertheless, 40 years since the introduction of CTG to clinical practice, its evaluation is stil...

OB HUB: Remote Electronic Fetal Monitoring Surveillance.

MCN. The American journal of maternal child nursing
OBJECTIVE: The purpose of this project was to implement a remote fetal surveillance unit with increased vigilance and timelier responses to electronic fetal monitor tracings to improve neonatal outcomes and increase safety.

[Research on intelligent fetal heart monitoring model based on deep active learning].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
Cardiotocography (CTG) is a non-invasive and important tool for diagnosing fetal distress during pregnancy. To meet the needs of intelligent fetal heart monitoring based on deep learning, this paper proposes a TWD-MOAL deep active learning algorithm ...

Concordance analysis of intrapartum cardiotocography between physicians and artificial intelligence-based technique using modified one-dimensional fully convolutional networks.

Journal of the Chinese Medical Association : JCMA
BACKGROUND: Cardiotocography is a common method of electronic fetal monitoring (EFM) for fetal well-being. Data-driven analyses have shown potential for automated EFM assessment. For this preliminary study, we used a novel artificial intelligence met...

Deep Learning for Continuous Electronic Fetal Monitoring in Labor.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Continuous electronic fetal monitoring (EFM) is used worldwide to visually assess whether a fetus is exhibiting signs of distress during labor, and may benefit from an emergency operative delivery (e.g. Cesarean section). Previously, computerized EFM...