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Fetus

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Transformer-Based Wavelet-Scalogram Deep Learning for Improved Seizure Pattern Recognition in Post-Hypoxic-Ischemic Fetal Sheep EEG.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Hypoxic-ischemic (HI) events in newborns can trigger seizures, which are highly associated with later neurodevelopmental impairment. The precise detection of these seizures is a complex task requiring considerable very specialized expertise, undersco...

Noninvasive fetal genotyping using deep neural networks.

Briefings in bioinformatics
Circulating cell-free DNA (cfDNA) is a powerful diagnostics tool that is widely studied in the context of liquid biopsy in oncology and other fields. In obstetrics, maternal plasma cfDNA have already proven its utility, enabling noninvasive prenatal ...

LPC-SonoNet: A Lightweight Network Based on SonoNet and Light Pyramid Convolution for Fetal Ultrasound Standard Plane Detection.

Sensors (Basel, Switzerland)
The detection of fetal ultrasound standard planes (FUSPs) is important for the diagnosis of fetal malformation and the prevention of perinatal death. As a promising deep-learning technique in FUSP detection, SonoNet's network parameters have a large ...

Novel neural network classification of maternal fetal ultrasound planes through optimized feature selection.

BMC medical imaging
Ultrasound (US) imaging is an essential diagnostic technique in prenatal care, enabling enhanced surveillance of fetal growth and development. Fetal ultrasonography standard planes are crucial for evaluating fetal development parameters and detecting...

Optimizing lipid nanoparticles for fetal gene delivery in vitro, ex vivo, and aided with machine learning.

Journal of controlled release : official journal of the Controlled Release Society
There is a clinical need to develop lipid nanoparticles (LNPs) to deliver congenital therapies to the fetus during pregnancy. The aim of these therapies is to restore normal fetal development and prevent irreversible conditions after birth. As a firs...

Automatic Measurement of Frontomaxillary Facial Angle in Fetal Ultrasound Images Using Deep Learning.

Sensors (Basel, Switzerland)
Accurate measurement of frontomaxillary facial (FMF) angles in prenatal ultrasound (US) scans plays a pivotal role in the screening of trisomy 21. Nevertheless, this intricate procedure heavily relies on the proficiency of the ultrasonographer and te...

Clinical validation of explainable AI for fetal growth scans through multi-level, cross-institutional prospective end-user evaluation.

Scientific reports
We aimed to develop and evaluate Explainable Artificial Intelligence (XAI) for fetal ultrasound using actionable concepts as feedback to end-users, using a prospective cross-center, multi-level approach. We developed, implemented, and tested a deep-l...

The Artificial Intelligence-Enhanced Echocardiographic Detection of Congenital Heart Defects in the Fetus: A Mini-Review.

Medicina (Kaunas, Lithuania)
Artificial intelligence (AI) is rapidly gaining attention in radiology and cardiology for accurately diagnosing structural heart disease. In this review paper, we first outline the technical background of AI and echocardiography and then present an a...

FetDTIAlign: A deep learning framework for affine and deformable registration of fetal brain dMRI.

NeuroImage
Diffusion MRI (dMRI) offers unique insights into the microstructure of fetal brain tissue in utero. Longitudinal and cross-sectional studies of fetal dMRI have the potential to reveal subtle but crucial changes associated with normal and abnormal neu...

TCGAN: Temporal Convolutional Generative Adversarial Network for Fetal ECG Extraction Using Single-Channel Abdominal ECG.

IEEE journal of biomedical and health informatics
Noninvasive fetal ECG (FECG) monitoring holds significant importance in ensuring the normal development of the fetus. Since FECG is usually submerged by maternal ECG (MECG) and background noise in abdominal ECG (AECG), it is challenging to exactly re...