ArticleFrontiers in physiology2019
Computer-Aided Diagnosis System of Fetal Hypoxia Incorporating Recurrence Plot With Convolutional Neural Network.
Article in Frontiers in physiology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers, 1 of them a synthesis that pooled it.
What it found
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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
24 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Non-linear Methods Predominant in Fetal Heart Rate Analysis: A Systematic Review.Frontiers in medicine · 2021Pooled it
- Machine learning based classification in obstetrics: evaluating models, partitioning strategies, and key predictors in cardiotocography.BMC pregnancy and childbirth · 2026Article
- Predicting Intrapartum Acidemia: A Review of Approaches Based on Fetal Heart Rate.Bioengineering (Basel, Switzerland) · 2026Review
- A multidimensional ensemble pipeline for early detection of IUGR condition through CTG.Frontiers in digital health · 2026Article
- Enhancing cardiotocography classification via ensemble learning and threshold optimization.Scientific reports · 2025Article
- Optimizing Fetal Surveillance in Fetal Growth Restriction: A Narrative Review of the Role of the Computerized Cardiotocographic Assessment.Journal of clinical medicine · 2025Review
- Review
- 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
- Cross-Database Evaluation of Deep Learning Methods for Intrapartum Cardiotocography Classification.IEEE journal of translational engineering in health and medicine · 2025Article
- Article
- Automatic classification of fetal heart rate based on a multi-scale LSTM network.Frontiers in physiology · 2024Article
- Computerised Cardiotocography Analysis for the Automated Detection of Fetal Compromise during Labour: A Review.Bioengineering (Basel, Switzerland) · 2023Review
- Real-time Classification of Fetal Status Based on Deep Learning and Cardiotocography Data.Journal of medical systems · 2023Article
- Multimodal Deep Learning for Predicting Adverse Birth Outcomes Based on Early Labour Data.Bioengineering (Basel, Switzerland) · 2023Article
- A lightweight fetal distress-assisted diagnosis model based on a cross-channel interactive attention mechanism.Frontiers in physiology · 2023Article
- Quantitative Analysis Using Consecutive Time Window for Unobtrusive Atrial Fibrillation Detection Based on Ballistocardiogram Signal.Sensors (Basel, Switzerland) · 2022Article
- Heart rate markers for prediction of fetal acidosis in an experimental study on fetal sheep.Scientific reports · 2022Article
- UNSUPERVISED CLUSTERING AND ANALYSIS OF CONTRACTION-DEPENDENT FETAL HEART RATE SEGMENTS.Proceedings of the ... IEEE International Conference on Acoustics, Speech, and Signal Processing. ICASSP (Conference) · 2022Article
- CTGNet: Automatic Analysis of Fetal Heart Rate from Cardiotocograph Using Artificial Intelligence.Maternal-fetal medicine (Wolters Kluwer Health, Inc.) · 2022Article
- Intrapartum cardiotocography trace pattern pre-processing, features extraction and fetal health condition diagnoses based on RCOG guideline.PeerJ. Computer science · 2022Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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Indexed as
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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.