Pregnancy

Radiomics-based ultrasOund Model for differentiating Uterine Sarcomas from leiomyomas (ROMUS): a retrospective pilot Multicenter Italian Trials in Ovarian Cancer (MITO) study.

OBJECTIVE: To develop machine-learning models that incorporate clinical information and radiomics fe...

Multilevel predictors of ultra-processed food intake in Canadian preschoolers.

BACKGROUND: Ultra-processed foods (UPF) dominate modern food systems and contribute significantly to...

Imidazolium Lipid-based Nanoparticles Enable Effective mRNA Delivery and Cellular Immune Response.

Imidazolium LipidBrick® cationic lipid nanoparticles (LNPs) provide a pH-independent alternative to ...

Smartphone Detection of Fetal Movements Using Artificial Intelligence.

OBJECTIVE: To evaluate whether machine learning could be used with audio recordings from a smartphon...

Associations of PM2.5 and PAHs from wildland fires with pregnancy outcomes: evidence based on high-resolution exposure assessment.

Wildfire threats are increasing dramatically and compromising decades of progress in air quality imp...

Multivariable AI-based analysis of immune-lifestyle patterns associated with recurrent pregnancy loss: an exploratory retrospective study.

Introduction Approximately 1-5% of pregnant women experience recurrent pregnancy loss (RPL). Early d...

Serum Element-Driven Gut Microbial Disturbances and Their Predictive Implications for Gestational Dyslipidemia: A Prospective Birth Cohort Study.

Pregnancy-triggered shifts in maternal serum elements and gut microbiota may disrupt metabolic balan...

Differentiation of Benign and Malignant Cervical Lymph Nodes Using a Multi-Modal Ultrasound-Based Machine Learning Model with SHAP Interpretability.

OBJECTIVES: To evaluate the diagnostic value of a machine learning (ML) model based on multi-modal u...

Artificial intelligence-enabled ultrasound diagnosis and stratification of follicular thyroid neoplasms: a multi-center study.

Preoperatively distinguishing follicular thyroid carcinoma (FTC) from follicular thyroid adenoma (FT...

Artificial intelligence-based coronary computed tomography angiography quantification of atherosclerosis burden: comparison with intravascular ultrasound in the INVICTUS Registry.

OBJECTIVES: Automated artificial intelligence (AI)-based assessment of atherosclerosis burden applie...

Maternal Gut Microbiome as a Predictor of Insulin Therapy Requirement in Gestational Diabetes.

BACKGROUND: Gestational diabetes mellitus (GDM) often requires pharmacological intervention beyond l...

Deconstruction and reconstruction of degrading effects in ultrasound imaging: aberration, multiple reverberation, and trailing reverberation.

Ultrasound image degradation in the human body arises from the propagation and reflection of acousti...

Hierarchical machine learning models for predicting antenatal care utilisation among Nigerian women: Identifying actionable insights for health policy.

Determinants of labor epidural analgesia uptake and associations with maternal-neonatal outcomes: a stratified cohort study with risk prediction modeling.

BACKGROUND: Labor pain is a major physiological and psychological stressor for women during childbir...

A deep-learning-based early warning system for abnormal eye conditions in chickens.

In current poultry production practice, farmers are required to frequently enter their poultry house...

Modeling strategies for CGM data: A scoping review of mechanistic, machine learning, and hybrid approaches in diabetes management.

BACKGROUND: The increasing availability of continuous glucose monitoring (CGM) data has opened new a...

Current Trends in Ultrasound Wearables: Spotlight on System Architecture.

Wearable ultrasound sensing systems are rapidly emerging for precise, continuous, and intuitive biom...

AI-Assisted Lung Sliding Detection in Point-of-Care Ultrasound by Marine Corps Corpsmen: A Multi-Reader Study.

BACKGROUND: Artificial intelligence (AI) has the potential to address training limitations and inter...

Integrating Reproductive and Clinical Variables to Predict Postpartum Disability Outcomes in Multiple Sclerosis Using Machine Learning.

BACKGROUND: Pregnancy represents a unique immunological state in women with multiple sclerosis (MS),...

Artificial Intelligence Integration in Radiation Therapy Education: A Multi-Modal Approach.

INTRODUCTION: Critical workforce shortages in radiation oncology have led tertiary institutions to r...

ARIMA-based forecasting of cerebral physiologic signals in acute traumatic brain injury: a CAnadian high-resolution TBI (CAHR-TBI) cohort study.

BACKGROUND: Traumatic brain injury (TBI) remains a major global health issue, with limited progress ...