AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Fetus

Showing 11 to 20 of 95 articles

Clear Filters

Investigation on ultrasound images for detection of fetal congenital heart defects.

Biomedical physics & engineering express
Congenital heart defects (CHD) are one of the serious problems that arise during pregnancy. Early CHD detection reduces death rates and morbidity but is hampered by the relatively low detection rates (i.e., 60%) of current screening technology. The d...

Enhancing Fetal Electrocardiogram Signal Extraction Accuracy through a CycleGAN Utilizing Combined CNN-BiLSTM Architecture.

Sensors (Basel, Switzerland)
The fetal electrocardiogram (FECG) records changes in the graph of fetal cardiac action potential during conduction, reflecting the developmental status of the fetus in utero and its physiological cardiac activity. Morphological alterations in the FE...

A novel artificial intelligence model for measuring fetal intracranial markers during the first trimester based on two-dimensional ultrasound image.

International journal of gynaecology and obstetrics: the official organ of the International Federation of Gynaecology and Obstetrics
OBJECTIVE: To establish reference ranges of fetal intracranial markers during the first trimester and develop the first novel artificial intelligence (AI) model to measure key markers automatically.

FetoML: Interpretable predictions of the fetotoxicity of drugs based on machine learning approaches.

Molecular informatics
Pregnant females may use medications to manage health problems that develop during pregnancy or that they had prior to pregnancy. However, using medications during pregnancy has a potential risk to the fetus. Assessing the fetotoxicity of drugs is es...

Rapid detection of fetal compromise using input length invariant deep learning on fetal heart rate signals.

Scientific reports
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...

Prediction of fetal brain gestational age using multihead attention with Xception.

Computers in biology and medicine
Accurate gestational age (GA) prediction is crucial for monitoring fetal development and ensuring optimal prenatal care. Traditional methods often face challenges in terms of precision and prediction efficiency. In this context, leveraging modern dee...

AI driven interpretable deep learning based fetal health classification.

SLAS technology
In this study, a deep learning model is proposed for the classification of fetal health into 3 categories: Normal, suspect, and pathological. The primary objective is to utilize the power of deep learning to improve the efficiency and effectiveness o...

MG-Net: A fetal brain tissue segmentation method based on multiscale feature fusion and graph convolution attention mechanisms.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Fetal brain tissue segmentation provides foundational support for comprehensively understanding the neurodevelopment of normal and congenital disease-affected fetuses. Manual labeling is very time-consuming, and automated se...

TKR-FSOD: Fetal Anatomical Structure Few-Shot Detection Utilizing Topological Knowledge Reasoning.

IEEE journal of biomedical and health informatics
Fetal multi-anatomical structure detection in ultrasound (US) images can clearly present the relationship and influence between anatomical structures, providing more comprehensive information about fetal organ structures and assisting sonographers in...