AIMC Topic: Prenatal Diagnosis
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Towards automatic US-MR fetal brain image registration with learning-based methods.
NeuroImage
Mar 7, 2025
Fetal brain imaging is essential for prenatal care, with ultrasound (US) and magnetic resonance imaging (MRI) providing complementary strengths. While MRI has superior soft tissue contrast, US offers portable and inexpensive screening of neurological...
Bridging gaps in artificial intelligence adoption for maternal-fetal and obstetric care: Unveiling transformative capabilities and challenges.
Computer methods and programs in biomedicine
Feb 23, 2025
PURPOSE: This review aims to comprehensively explore the application of Artificial Intelligence (AI) to an area that has not been traditionally explored in depth: the continuum of maternal-fetal health. In doing so, the intent was to examine this phy...
Precision fetal cardiology detects cyanotic congenital heart disease using maternal saliva metabolome and artificial intelligence.
Scientific reports
Jan 15, 2025
Prenatal sonographic diagnosis of congenital heart disease (CHD) can lead to improved morbidity and mortality. However, the diagnostic accuracy of ultrasound, the sole prenatal screening tool, remains limited. Failed prenatal or early newborn detecti...
Self-learning neural network as a prediction model in non-invasive prenatal testing to detect fetal SNVs.
Journal of translational medicine
Jul 30, 2024
Prediction of chromosomal abnormalities in the screening of the first trimester of pregnancy using machine learning methods: a study protocol.
Reproductive health
Jul 3, 2024
BACKGROUND: For women in the first trimester, amniocentesis or chorionic villus sampling is recommended for screening. Machine learning has shown increased accuracy over time and finds numerous applications in enhancing decision-making, patient care,...
Machine learning in prenatal MRI predicts postnatal ventricular abnormalities in fetuses with isolated ventriculomegaly.
European radiology
May 10, 2024
OBJECTIVES: To evaluate the intracranial structures and brain parenchyma radiomics surrounding the occipital horn of the lateral ventricle in normal fetuses (NFs) and fetuses with ventriculomegaly (FVs), as well as to predict postnatally enlarged lat...
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...
Validation of the first-trimester machine learning model for predicting pre-eclampsia in an Asian population.
International journal of gynaecology and obstetrics: the official organ of the International Federation of Gynaecology and Obstetrics
Apr 26, 2024
OBJECTIVES: To evaluate the performance of an artificial intelligence (AI) and machine learning (ML) model for first-trimester screening for pre-eclampsia in a large Asian population.
Deep learning prediction of renal anomalies for prenatal ultrasound diagnosis.
Scientific reports
Apr 19, 2024
Deep learning algorithms have demonstrated remarkable potential in clinical diagnostics, particularly in the field of medical imaging. In this study, we investigated the application of deep learning models in early detection of fetal kidney anomalies...
Artificial intelligence-based diagnosis in fetal pathology using external ear shapes.
Prenatal diagnosis
Apr 18, 2024
OBJECTIVE: Here we trained an automatic phenotype assessment tool to recognize syndromic ears in two syndromes in fetuses-=CHARGE and Mandibulo-Facial Dysostosis Guion Almeida type (MFDGA)-versus controls.
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