AIMC Topic: Heart Rate, Fetal
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Integrating machine learning techniques and physiology based heart rate features for antepartum fetal monitoring.
Computer methods and programs in biomedicine
Oct 17, 2019
BACKGROUND AND OBJECTIVES: Intrauterine Growth Restriction (IUGR) is a fetal condition defined as the abnormal rate of fetal growth. The pathology is a documented cause of fetal and neonatal morbidity and mortality. In clinical practice, diagnosis is...
Use of artificial intelligence (AI) in the interpretation of intrapartum fetal heart rate (FHR) tracings: a systematic review and meta-analysis.
Archives of gynecology and obstetrics
May 3, 2019
OBJECTIVES: To determine the degree of inter-rater reliability (IRR) between human and artificial intelligence (AI) interpretation of fetal heart rate tracings (FHR), and to determine whether AI-assisted electronic fetal monitoring interpretation imp...
The Design and Implementation of Cardiotocography Signals Classification Algorithm Based on Neural Network.
Computational and mathematical methods in medicine
Dec 3, 2018
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
Jun 6, 2018
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
Dec 8, 2017
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
Jul 6, 2017
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...
Sparse Support Vector Machine for Intrapartum Fetal Heart Rate Classification.
IEEE journal of biomedical and health informatics
Mar 24, 2016
Fetal heart rate (FHR) monitoring is routinely used in clinical practice to help obstetricians assess fetal health status during delivery. However, early detection of fetal acidosis that allows relevant decisions for operative delivery remains a chal...
Combining latent class analysis labeling with multiclass approach for fetal heart rate categorization.
Physiological measurement
Apr 20, 2015
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...
n-Order and maximum fuzzy similarity entropy for discrimination of signals of different complexity: Application to fetal heart rate signals.
Computers in biology and medicine
Mar 17, 2015
This paper presents two new concepts for discrimination of signals of different complexity. The first focused initially on solving the problem of setting entropy descriptors by varying the pattern size instead of the tolerance. This led to the search...
[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
Feb 25, 2025
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 ...
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