AIMC Topic: Heart Rate, Fetal
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AI-Driven fetal distress monitoring SDN-IoMT networks.
PloS one
Jul 31, 2025
The healthcare industry is transforming with the integration of the Internet of Medical Things (IoMT) with AI-powered networks for improved clinical connectivity and advanced monitoring capabilities. However, IoMT devices struggle with traditional ne...
An AI method to predict pregnancy loss by extracting biological indicators from embryo ultrasound recordings in early pregnancy.
Scientific reports
Jul 17, 2025
B-ultrasound results are widely used in early pregnancy loss (EPL) prediction, but there are inevitable intra-observer and inter-observer errors in B-ultrasound results especially in early pregnancy, which lead to inconsistent assessment of embryonic...
Automated interpretation of cardiotocography using deep learning in a nationwide multicenter study.
Scientific reports
Jun 4, 2025
Timely detection of abnormal cardiotocography (CTG) during labor plays a crucial role in enhancing fetal prognosis. Recent research has explored the use of deep learning for CTG interpretation, most studies rely on small, localized datasets or focus ...
Extraction of fetal heartbeat locations in abdominal phonocardiograms using deep attention transformer.
Computers in biology and medicine
Mar 16, 2025
Assessing fetal health traditionally involves techniques like echocardiography, which require skilled professionals and specialized equipment, making them unsuitable for low-resource settings. An emerging alternative is Phonocardiography (PCG), which...
Predicting vaginal delivery after labor induction using machine learning: Development of a multivariable prediction model.
Acta obstetricia et gynecologica Scandinavica
Nov 27, 2024
INTRODUCTION: Induction of labor, often used for pregnancy termination, has globally rising rates, especially in high-income countries where pregnant women present with more comorbidities. Consequently, concerns on a potential rise in cesarean sectio...
A multimodal deep learning-based algorithm for specific fetal heart rate events detection.
Biomedizinische Technik. Biomedical engineering
Nov 4, 2024
OBJECTIVES: This study aims to develop a multimodal deep learning-based algorithm for detecting specific fetal heart rate (FHR) events, to enhance automatic monitoring and intelligent assessment of fetal well-being.
A Pragmatic Approach to Fetal Monitoring via Cardiotocography Using Feature Elimination and Hyperparameter Optimization.
Interdisciplinary sciences, computational life sciences
Oct 5, 2024
Cardiotocography (CTG) is used to assess the health of the fetus during birth or antenatally in the third trimester. It concurrently detects the maternal uterine contractions (UC) and fetal heart rate (FHR). Fetal distress, which may require therapeu...
Rapid detection of fetal compromise using input length invariant deep learning on fetal heart rate signals.
Scientific reports
Jun 1, 2024
Standard clinical practice to assess fetal well-being during labour utilises monitoring of the fetal heart rate (FHR) using cardiotocography. However, visual evaluation of FHR signals can result in subjective interpretations leading to inter and intr...
Intrapartum electronic fetal heart rate monitoring to predict acidemia at birth with the use of deep learning.
American journal of obstetrics and gynecology
Apr 24, 2024
BACKGROUND: Electronic fetal monitoring is used in most US hospital births but has significant limitations in achieving its intended goal of preventing intrapartum hypoxic-ischemic injury. Novel deep learning techniques can improve complex data proce...
Identifying fetal status with fetal heart rate: Deep learning approach based on long convolution.
Computers in biology and medicine
Apr 21, 2023
CTG (Cardiotocography) is an effective tool for fetal status assessment. Clinically, doctors mainly evaluate the health of fetus by observing FHR (fetal heart rate). The rapid development of Artificial Intelligence has led realization of computer-aid...
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