Pregnancy

Emerging applications of artificial intelligence for obstetric ultrasound: A scoping review.

BACKGROUND: The WHO recommends that all pregnant women receive an ultrasound (US) scan prior to 24 weeks gestation to encourage early identification of various conditions, such as fetal anomalies, multiple gestation, and placental abnormalities; however, global access to US remains limited. This has prompted many research groups to develop artificial intelligence (AI) approaches for obstetric US. ...

Artificial intelligence application in the prediction of spontaneous preterm birth by cervical length in the first trimester of pregnancy: Comparison of three measurement methods.

OBJECTIVES: The current study evaluates the efficacy of artificial intelligence (AI)-assisted measurement of cervical length (CL) in predicting spontaneous preterm birth (sPTB), comparing the traditional single-line and two-line methods with the innovative AI-line method in the first trimester of pregnancy. MATERIALS AND METHODS: This study is a retrospective secondary analysis of ultrasound image...

Multicenter Evaluation of an Artificial Intelligence System for Automatic Recognition of Fetal Ultrasound Findings Suggestive of Congenital Malformations.

OBJECTIVE: To evaluate the diagnostic performance of an artificial intelligence (AI) system for detecting eight abnormal fetal ultrasound findings acr...

Diagnostic Accuracy of Artificial Intelligence in Detecting Pleural Effusion on Ultrasound Imaging: A Systematic Review and Meta-Analysis.

Artificial intelligence (AI) interpretation of ultrasound (US) images is promising, yet its accuracy in diagnosing pleural effusions remains unclear. ...

Wavelet-Based Frequency Replacement and Edge Enhancement for Semi-Supervised Fetal Ultrasound Image Segmentation.

OBJECTIVES: Ultrasound image segmentation remains a significant challenge due to inherent low contrast and blurred anatomical boundaries. Fully superv...

UltraMN: Advancing Real-Time Median Nerve Ultrasound Monitoring With a Multitask Deep Learning Framework.

OBJECTIVE: This study aims to develop an advanced deep learning framework to overcome the challenges associated with real-time ultrasound monitoring o...

Machine learning-based identification of determinants of pulse pressure in pregnant women.

BACKGROUND: Pulse pressure (PP) is an important marker of arterial stiffness and cardiovascular risk during pregnancy, yet its longitudinal determinan...

Emerging Diagnostic Indications for Endoscopic Ultrasound.

Endoscopic ultrasound (EUS) has evolved from a diagnostic imaging tool into a versatile platform that enables high-precision access, sampling, and the...

Metabolic profiling of the maternal liver in pregnant mice exposed to Di(2-ethylhexyl) phthalate (DEHP).

In this study, pregnant mice were exposed to dietary Di(2-ethylhexyl) phthalate (DEHP) (0.1 % or 0.2 %) from gestational day (GD) 0 to GD18, and mater...

Programmable lipid nanoparticles for RNA therapeutics: Design principles and clinical translation.

RNA therapeutics have come of age as clinically validated modalities including mRNA, siRNA, antisense oligonucleotides (ASOs), and in vivo genome edit...

Developing an artificial intelligence-powered question-and-answer chatbot with English-Spanish capabilities for new mothers.

OBJECTIVES: Generative AI chatbots are revolutionizing health education by making complex information more accessible to the public. However, their us...

AI-enhanced virtual reality simulation for nursing students' empathy: Automated scoring and inter-rater reliability in a randomised controlled study.

BACKGROUND: Empathy is a fundamental nursing competence that supports effective communication and high-quality care. In obstetric settings, the emotio...

Multimodal Convolutional Neural Network Model for Evaluating Development of Fetal Rabbit Lung Using B-mode and Shear Wave Elastography Ultrasound Images.

OBJECTIVE: To evaluate the performance of convolutional neural network (CNN)-based models for predicting fetal rabbit lung development: unimodal model...

Classification of Salivary Gland Tumors on Ultrasound Using Artificial Intelligence: A Systematic Review and Meta-Analysis.

OBJECTIVE: Accurate classification of salivary gland tumors is critical to guiding appropriate management. This study evaluates the diagnostic perform...

Automated active learning to optimize hydrogel drug release profiles.

Hydrogels are widely used in drug delivery due to their biocompatibility and tunable release properties. However, optimizing hydrogel formulations to ...

Artificial intelligence in academic research publishing: updates, controversies, and considerations for pregnancy and perinatal research.

Artificial intelligence (AI) has rapidly transformed academic writing and publishing, progressing from simple grammar checkers and citation tools to s...

Evaluating the efficacy and diagnostic reliability of computer vision artificial intelligence algorithm in automating anatomical classification for second-trimester fetal anomaly ultrasound scans: A prospective cohort study.

OBJECTIVE: To evaluate the diagnostic accuracy and workflow efficiency of BioticsAI-anatomyUNet-0.1-2022 software in identifying 18 standard fetal ana...

Antimicrobial peptides-based strategies at the frontline in battling the escalating menace of methicillin-resistant Staphylococcus aureus biofilms.

Antimicrobial resistance (AMR), particularly in methicillin-resistant Staphylococcus aureus (MRSA), continues to threaten global health due to its mul...

Evaluation of machine learning predictions for early reproductive success in commercial US dairies.

Reproductive performance affects the profitability of a dairy herd. The ability to understand the reproductive capabilities of individual cows and the...

Degraders on Demand: Engineering Smart Nanocarriers for PROTAC Delivery.

Proteolysis-targeting chimeras (PROTACs) are transforming targeted therapeutics by enabling the selective and catalytic degradation of disease-associa...