ReviewBioengineering (Basel, Switzerland)2023
Computerised Cardiotocography Analysis for the Automated Detection of Fetal Compromise during Labour: A Review.
Review in Bioengineering (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
17 citing papers in PubMed, 36 citations in OpenAlex.
- Enhancing agreement in cardiotocography interpretation between midwives and obstetricians through a rule-based AI program: A comparative cross-sectional study.International journal of gynaecology and obstetrics: the official organ of the International Federation of Gynaecology and Obstetrics · 2026Article
- Fetal health classification: a deep learning model with enhanced interpretability and lightweight deployment.Medical & biological engineering & computing · 2026Article
- Artificial intelligence-based prediction of fetal hypoxia: a multicenter model development and nationwide AI-human comparison.BMC medicine · 2026Article
- Randomised study of human machine collaboration for cardiotocography interpretation during labour.NPJ digital medicine · 2026Article
- Addressing Class Imbalance in Fetal Health Classification: Rigorous Benchmarking of Multi-Class Resampling Methods on Cardiotocography Data.Diagnostics (Basel, Switzerland) · 2026Article
- Assessing signal loss, accuracy, and acceptability of an ambulatory fetal electrocardiography with cardiotocography in the antepartum and intrapartum phases.Acta obstetricia et gynecologica Scandinavica · 2026Article
- Predicting Intrapartum Acidemia: A Review of Approaches Based on Fetal Heart Rate.Bioengineering (Basel, Switzerland) · 2026Review
- Association of normal-range fetal heart rate variations during labor with umbilical cord arterial blood gas parameters and neonatal outcomes: A cross-sectional study.International journal of reproductive biomedicine · 2025Article
- Impact of missing electronic fetal monitoring signals on perinatal asphyxia: a multicohort analysis.NPJ digital medicine · 2025Article
- Development of a novel artificial intelligence algorithm for interpreting fetal heart rate and uterine activity data in cardiotocography.Frontiers in digital health · 2025Article
- Cross-Database Evaluation of Deep Learning Methods for Intrapartum Cardiotocography Classification.IEEE journal of translational engineering in health and medicine · 2025Article
- A Pragmatic Approach to Fetal Monitoring via Cardiotocography Using Feature Elimination and Hyperparameter Optimization.Interdisciplinary sciences, computational life sciences · 2024Article
- Characteristics of phase synchronization in electrohysterography and tocodynamometry for preterm birth prediction.Heliyon · 2024Article
- Construction of a comprehensive fetal monitoring database for the study of perinatal hypoxic ischemic encephalopathy.MethodsX · 2024Article
- Rapid detection of fetal compromise using input length invariant deep learning on fetal heart rate signals.Scientific reports · 2024Article
- Fetal Heart Rate Preprocessing Techniques: A Scoping Review.Bioengineering (Basel, Switzerland) · 2024Article
- Editorial: New technologies improve maternal and newborn safety.Frontiers in medical technology · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 1 institution in 1 country.
Funding
Abstract
The measurement and analysis of fetal heart rate (FHR) and uterine contraction (UC) patterns, known as cardiotocography (CTG), is a key technology for detecting fetal compromise during labour. This technology is commonly used by clinicians to make decisions on the mode of delivery to minimise adverse outcomes. A range of computerised CTG analysis techniques have been proposed to overcome the limitations of manual clinician interpretation. While these automated techniques can potentially improve patient outcomes, their adoption into clinical practice remains limited. This review provides an overview of current FHR and UC monitoring technologies, public and private CTG datasets, pre-processing steps, and classification algorithms used in automated approaches for fetal compromise detection. It aims to highlight challenges inhibiting the translation of automated CTG analysis methods from research to clinical application and provide recommendations to overcome them.
Indexed as
Identifiers
What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.