Pregnancy

Semi-Supervised Thyroid Nodule Detection in Ultrasound Videos.

Deep learning techniques have been investigated for the computer-aided diagnosis of thyroid nodules ...

Machine learning-enhanced noninvasive prenatal testing of monogenic disorders.

OBJECTIVE: Single-nucleotide variants (SNVs) are of great significance in prenatal diagnosis as they...

Fetal bladder rupture after high-dose maternal opioid treatment: a case report.

OBJECTIVES: Fetal bladder rupture is rare and mainly caused by lower urinary tract obstruction (LUTO...

Can oral microbiome predict low birth weight infant delivery?

OBJECTIVES: This study aimed to identify the oral microbiota factors contributing to low birth weigh...

Enhancing Healthcare through Sensor-Enabled Digital Twins in Smart Environments: A Comprehensive Analysis.

This comprehensive review investigates the transformative potential of sensor-driven digital twin te...

Validation of the first-trimester machine learning model for predicting pre-eclampsia in an Asian population.

OBJECTIVES: To evaluate the performance of an artificial intelligence (AI) and machine learning (ML)...

Deep learning microstructure estimation of developing brains from diffusion MRI: A newborn and fetal study.

Diffusion-weighted magnetic resonance imaging (dMRI) is widely used to assess the brain white matter...

Intrapartum electronic fetal heart rate monitoring to predict acidemia at birth with the use of deep learning.

BACKGROUND: Electronic fetal monitoring is used in most US hospital births but has significant limit...

Exploring the Limits of Artificial Intelligence for Referencing Scientific Articles.

OBJECTIVE:  To evaluate the reliability of three artificial intelligence (AI) chatbots (ChatGPT, Goo...

Use of natural language processing to uncover racial bias in obstetrical documentation.

Natural Language Processing (NLP), a form of Artificial Intelligence, allows free-text based clinica...

Autonomous fetal morphology scan: deep learning + clustering merger - the second pair of eyes behind the doctor.

The main cause of fetal death, of infant morbidity or mortality during childhood years is attributed...

Deep learning prediction of renal anomalies for prenatal ultrasound diagnosis.

Deep learning algorithms have demonstrated remarkable potential in clinical diagnostics, particularl...

Computer-Aided Diagnosis of Duchenne Muscular Dystrophy Based on Texture Pattern Recognition on Ultrasound Images Using Unsupervised Clustering Algorithms and Deep Learning.

OBJECTIVE: The feasibility of using deep learning in ultrasound imaging to predict the ambulatory st...

Teacher-student guided knowledge distillation for unsupervised convolutional neural network-based speckle tracking in ultrasound strain elastography.

Accurate and efficient motion estimation is a crucial component of real-time ultrasound elastography...

The combination of deep learning and pseudo-MS image improves the applicability of metabolomics to congenital heart defect prenatal screening.

To investigate the metabolic alterations in maternal individuals with fetal congenital heart disease...

Exploring the potential of machine learning in gynecological care: a review.

Gynecological health remains a critical aspect of women's overall well-being, with profound implicat...

Artificial intelligence in obstetric anaesthesia: an unlikely player?

Deep neural network (DNN) modelling for prediction of the mode of delivery.

One of the factors that worry obstetricians the most is the method of delivery. In recent years, the...

MSK-TIM: A Telerobotic Ultrasound System for Assessing the Musculoskeletal System.

The aim of this paper is to investigate technological advancements made to a robotic tele-ultrasound...

A Dempster-Shafer Approach to Trustworthy AI With Application to Fetal Brain MRI Segmentation.

Deep learning models for medical image segmentation can fail unexpectedly and spectacularly for path...

Classifying early infant feeding status from clinical notes using natural language processing and machine learning.

The objective of this study is to develop and evaluate natural language processing (NLP) and machine...