ArticleHealth and technology2017
Investigating pH based evaluation of fetal heart rate (FHR) recordings.
Article in Health and technology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 1 of them a synthesis that pooled it.
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
21 citing papers in PubMed, 1 synthesis or guideline pooled it, 59 citations in OpenAlex.
- Non-linear Methods Predominant in Fetal Heart Rate Analysis: A Systematic Review.Frontiers in medicine · 2021Pooled it
- Predicting Intrapartum Acidemia: A Review of Approaches Based on Fetal Heart Rate.Bioengineering (Basel, Switzerland) · 2026Review
- Objective interpretation of intrapartum cardiotocography images using attention-guided convolutional neural networks.Frontiers in pediatrics · 2026Article
- Automated interpretation of cardiotocography using deep learning in a nationwide multicenter study.Scientific reports · 2025Article
- Advancements in Fetal Heart Rate Monitoring: A Report on Opportunities and Strategic Initiatives for Better Intrapartum Care.BJOG : an international journal of obstetrics and gynaecology · 2025Review
- AI-augmented prenatal care: a dual-modal fetal health assessment system integrating cardiotocography and uterine contraction synergy.Frontiers in physiology · 2025Article
- Fetal Heart Rate Preprocessing Techniques: A Scoping Review.Bioengineering (Basel, Switzerland) · 2024Article
- A hybrid stacked ensemble and Kernel SHAP-based model for intelligent cardiotocography classification and interpretability.BMC medical informatics and decision making · 2023Article
- Computerised Cardiotocography Analysis for the Automated Detection of Fetal Compromise during Labour: A Review.Bioengineering (Basel, Switzerland) · 2023Review
- A lightweight fetal distress-assisted diagnosis model based on a cross-channel interactive attention mechanism.Frontiers in physiology · 2023Article
- Deep learning based fetal distress detection from time frequency representation of cardiotocogram signal using Morse wavelet: research study.BMC medical informatics and decision making · 2022Article
- BOOST ENSEMBLE LEARNING FOR CLASSIFICATION OF CTG SIGNALS.Proceedings of the ... IEEE International Conference on Acoustics, Speech, and Signal Processing. ICASSP (Conference) · 2022Article
- Cardiotocography analysis by empirical dynamic modeling and Gaussian processes.Frontiers in bioengineering and biotechnology · 2022Article
- Unsupervised Detection of Anomalies in Fetal Heart Rate Tracings using Phase Space Reconstruction.Proceedings of the ... European Signal Processing Conference (EUSIPCO). EUSIPCO (Conference) · 2021Article
- Comparison of Multivariable Logistic Regression and Other Machine Learning Algorithms for Prognostic Prediction Studies in Pregnancy Care: Systematic Review and Meta-Analysis.JMIR medical informatics · 2020Review
- Estimation of Consecutively Missed Samples in Fetal Heart Rate Recordings.Proceedings of the ... European Signal Processing Conference (EUSIPCO). EUSIPCO (Conference) · 2020Article
- DeepFHR: intelligent prediction of fetal Acidemia using fetal heart rate signals based on convolutional neural network.BMC medical informatics and decision making · 2019Review
- Prediction of intrapartum fetal hypoxia considering feature selection algorithms and machine learning models.Health information science and systems · 2019Article
- [Intelligent fetal state assessment based on genetic algorithm and least square support vector machine].Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi · 2019Article
- Computer-Aided Diagnosis System of Fetal Hypoxia Incorporating Recurrence Plot With Convolutional Neural Network.Frontiers in physiology · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 3 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Cardiotocography (CTG) is a standard tool for the assessment of fetal well-being during pregnancy and delivery. However, its interpretation is associated with high inter- and intra-observer variability. Since its introduction there have been numerous attempts to develop computerized systems assisting the evaluation of the CTG recording. Nevertheless these systems are still hardly used in a delivery ward. Two main approaches to computerized evaluation are encountered in the literature; the first one emulates existing guidelines, while the second one is more of a data-driven approach using signal processing and computational methods. The latter employs preprocessing, feature extraction/selection and a classifier that discriminates between two or more classes/conditions. These classes are often formed using the umbilical cord artery pH value measured after delivery. In this work an approach to Fetal Heart Rate (FHR) classification using pH is presented that could serve as a benchmark for reporting results on the unique open-access CTU-UHB CTG database, the largest and the only freely available database of this kind. The overall results using a very small number of features and a Least Squares Support Vector Machine (LS-SVM) classifier, are in accordance to the ones encountered in the literature and outperform the results of a baseline classification scheme proving the utility of using advanced data processing methods. Therefore the achieved results can be used as a benchmark for future research involving more informative features and/or better classification algorithms.
Indexed as
Identifiers
What OpenQuestion 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 OpenQuestion graph.