Pregnancy

Long-term alterations of cerebellar structure after premature birth.

BACKGROUND: Alterations of cerebellar volume were reported in prematurely-born children, adolescents and adults, suggesting long-lasting effects on cerebellar growth. However, studies mostly examined global cerebellar volumes, which could disguise focal, subregional differences. METHODS: Based on T1-/T2-weighted MRI, this voxel-based morphometry study used the SUIT toolbox for optimized analysis o...

Artificial intelligence-based multi-modal multi-tasks analysis of thyroid ultrasound image features predicts thyroid cancer: a multicenter study.

Thyroid nodule ultrasound (US) images and their features are of great importance in thyroid nodule diagnosis, and can be helpful for radiologists' clinical decision-making. To evaluate whether an AI-assisted system can accurately characterize thyroid nodule ultrasound features and assist radiologists in diagnosing thyroid cancer. The AI-assisted system (MDT-TC) was trained and internally validated...

Direct Annotation of Unstructured Clinical Progress Notes Describes Postpartum Healthcare Needs and Encounter Characteristics of Women Whose Newborns Are Immediately Hospitalized in Intensive Care.

BACKGROUND: Among children's hospitals with integrated high-risk prenatal care and birthing facilities, the reasons for postpartum care-seeking, and d...

Reassurance-Focused First-Trimester Euploidy Screening With Machine Learning.

OBJECTIVE: To develop and internally validate a machine-learning (ML) model for first-trimester screening that prioritizes fetal euploidy reassurance ...

Next-generation epidermal patches: Bridging 3D and multidimensional printing for biomedical and personal care innovations.

Advances in additive manufacturing, particularly 3D and multidimensional printing, have enabled unprecedented control over the architecture, compositi...

Integration of advanced ultrasound techniques, radiomics, and artificial intelligence for improved diagnosis of cystic breast lesions.

Cystic breast lesions are commonly encountered on breast ultrasound, encompassing a spectrum from simple benign cysts to complex mixed solid and cysti...

Development of an Integrated Deep Learning Approach for Detecting Fetal Brain Abnormalities in Routine Second Trimester Ultrasound Scan: A Multicenter Study.

Purpose To develop and validate an anatomy-aware, two-stage, end-to-end deep learning (DL) pipeline for fetal brain abnormality automated detection on...

FetalSleepNet: A Transfer Learning Framework with Spectral Equalisation Domain Adaptation for Fetal Sleep State Classification.

OBJECTIVE: Fetal sleep state classification is essential for identifying neurodevelopmental complications like hypoxia, but manual annotation is subje...

Impact of multimodal information on the estimation of fetal growth indicators using machine learning regression models.

Accurate estimation of fetal growth indicators such as birth weight, birth length, and gestational age at birth is essential for monitoring pregnancy ...

Single-cell spatiotemporal dissection of the human maternal-fetal interface.

The human maternal-fetal interface is characterized by mosaic intermingling of maternal and fetal cells1. Yet the underlying cellular, molecular and s...

Functional Reclassification of Lipid-Based Drug Delivery Systems and Advances in Formulation Strategies and Manufacturing Challenges.

Lipid-based drug delivery systems have progressed from a simple empirical solubilization tool towards a highly precise engineered platform, capable of...

Segment anything small for ultrasound: Enhancing segmentation with non-generative augmentation.

Accurate segmentation of anatomical structures in ultrasound (US) images, particularly small ones, is challenging due to noise and variability in imag...

Automatic detection of the fetal brain midsagittal plane on MRI using a deep learning pipeline.

BACKGROUND: Accurate localization of the midsagittal plane (MSP) is essential for evaluating midline brain structures such as the corpus callosum and ...

Predictive performance of artificial intelligence algorithms for gestational diabetes mellitus in pregnant women: a protocol for systematic review and meta-analysis.

BACKGROUND: Gestational diabetes mellitus (GDM) is a prevalent pregnancy complication that can pose numerous adverse health effects on both mothers an...

Feasibility study of ultrasound-guided, power-assisted needle insertion for hemodialysis cannulation using an innovative, handheld device.

BACKGROUND: Vascular access (VA) for hemodialysis is achieved through arteriovenous fistulas (AVF), arteriovenous grafts (AVG), or central venous acce...

EFSUMB Guidelines on Multiparametric Ultrasound Thyroid Nodule Evaluation: PART I.

Thyroid nodules are common incidental findings, but only a small proportion of cases are malignant (4-6.5%) or symptomatic. Numerous follow-up examina...

EFSUMB Guidelines on Multiparametric Ultrasound Thyroid Nodule Evaluation: PART II.

Thyroid nodules are common incidental findings but only a small proportion of cases are malignant (4-6.5%) or symptomatic. Numerous follow-up examinat...

Innovation in intensive care: a framework to turn ideas and concepts into actionable solutions.

INTRODUCTION: Intensive care is under increasing pressure due to demographic changes, availability of new complex therapies, and workforce shortages, ...

Carotid Imaging: Current Concepts and Advanced Imaging.

Carotid atherosclerosis is a major cause of ischemic stroke, historically managed according to luminal stenosis severity. However, stenosis alone fail...

Artificial Intelligence-Aided Lung Ultrasound Detection of Interstitial Lung Disease in Systemic Sclerosis and Inflammatory Myopathy.

BACKGROUND: Lung ultrasound (LUS) is a sensitive, low-cost, and radiation-free modality for ILD detection. We previously developed and validated LUS i...