AIMC Topic: Fetal Diseases
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Deep learning for fetal inflammatory response diagnosis in the umbilical cord.
Placenta
Apr 24, 2025
INTRODUCTION: Inflammation of the umbilical cord can be seen as a result of ascending intrauterine infection or other inflammatory stimuli. Acute fetal inflammatory response (FIR) is characterized by infiltration of the umbilical cord by fetal neutro...
Machine Learning to Predict Outcomes of Fetal Cardiac Disease: A Pilot Study.
Pediatric cardiology
May 9, 2024
Prediction of outcomes following a prenatal diagnosis of congenital heart disease (CHD) is challenging. Machine learning (ML) algorithms may be used to reduce clinical uncertainty and improve prognostic accuracy. We performed a pilot study to train M...
Detection of maternal and fetal stress from the electrocardiogram with self-supervised representation learning.
Scientific reports
Dec 17, 2021
In the pregnant mother and her fetus, chronic prenatal stress results in entrainment of the fetal heartbeat by the maternal heartbeat, quantified by the fetal stress index (FSI). Deep learning (DL) is capable of pattern detection in complex medical d...
DeepFHR: intelligent prediction of fetal Acidemia using fetal heart rate signals based on convolutional neural network.
BMC medical informatics and decision making
Dec 30, 2019
BACKGROUND: Fetal heart rate (FHR) monitoring is a screening tool used by obstetricians to evaluate the fetal state. Because of the complexity and non-linearity, a visual interpretation of FHR signals using common guidelines usually results in signif...
A metabolomics-based approach for non-invasive screening of fetal central nervous system anomalies.
Metabolomics : Official journal of the Metabolomic Society
May 25, 2018
BACKGROUND: Central nervous system anomalies represent a wide range of congenital birth defects, with an incidence of approximately 1% of all births. They are currently diagnosed using ultrasound evaluation. However, there is strong need for a more a...
Detection of abnormalities in ultrasound lung image using multi-level RVM classification.
The journal of maternal-fetal & neonatal medicine : the official journal of the European Association of Perinatal Medicine, the Federation of Asia and Oceania Perinatal Societies, the International Society of Perinatal Obstetricians
Jul 30, 2015
The classification of abnormalities in ultrasound images is the monitoring tool of fluid to air passage in the lung. In this study, the adaptive median filtering technique is employed for the preprocessing step. The preprocessed image is then extract...
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