Pregnancy

Platelets as Programmable Drug Depots: Toward Predictive and Mechanistic Drug Loading.

Efficient drug delivery remains a major challenge in pharmaceutical science, with synthetic nanocarriers often facing limitations in real biological systems. While blood platelets have been explored as biomimetic carriers, their intrinsic capacity for molecular storage and stimulus-triggered release remains largely underutilized. Here, we propose that platelet granules can be viewed as programmabl...

Machine learning identification of maternal inflammatory response and systemic inflammatory response from placental membrane whole slide images.

INTRODUCTION: The placenta forms a critical barrier to infection through pregnancy, labor and, delivery. Acute placental inflammation in the membranes, diagnosed as Maternal Inflammatory Response (MIR), has short-term, and long-term consequences for offspring health. Digital pathology and machine learning can play an important role in understanding placental inflammation. The goal of this work is ...

Development of an interpretable machine learning model for predicting stress urinary incontinence following the delivery of a first child.

INTRODUCTION: The goal of this research is to use machine learning (ML) techniques to create a risk prediction model for postpartum stress urinary inc...

Integrating AI into hospital workflows: implementation strategies and real-world barriers.

Artificial intelligence (AI) is increasingly being integrated into hospital systems with the potential to transform clinical workflows, operational ef...

Transgene-free genome editing in plants.

Genome-editing tools for the precise, efficient modification of DNA have led to groundbreaking advances in crop improvement and basic plant science re...

Subgroup-Based Meta-Learning with Domain-Specific Self-Supervised Learning for Sarcopenia Detection from Musculoskeletal Ultrasound.

Sarcopenia is a progressive muscle disorder linked to aging, frailty, and increased healthcare burden. While ultrasound imaging offers a practical and...

Artificial Intelligence-Based Prediction of Progression from Gestational Diabetes to Type 2 Diabetes.

Women with a history of gestational diabetes mellitus (GDM) are at elevated risk of developing type 2 diabetes mellitus (T2DM) postpartum. This study ...

Machine Learning Prediction of Growth Hormone Response in Children Non-Growth Hormone-Deficient Short Stature.

Height gain under recombinant human growth hormone (rhGH) varies widely in children with short stature, making early, reliable response prediction ess...

Integration and Harmonization of Multi-Source Obstetric Data Using Rule-Based NLP for Fetomaternal Risk Modelling.

More than 80% of pregnancies in Germany are classified as high risk, leading to inefficient resource allocation. Although data-driven approaches could...

U-CBAMNet: an attention-guided deep learning model for accurate and explainable prediction of HER2 expression from breast ultrasound cine videos.

BACKGROUND: Accurate assessment of human epidermal growth factor receptor 2 (HER2) expression is essential for guiding targeted therapy in breast canc...

Automated ultrasound with AI for osteophyte grading in hand osteoarthritis: comparison with expert rheumatologist assessment.

BACKGROUND: The objective of this study was to characterise the agreement of the CE-certified automated robotic ultrasound system ARTHUR v.2.0, combin...

Emerging frontiers in genome editing: From CRISPR to next-generation technologies.

Genome editing has revolutionized molecular biology. It offers precise modification of genetic material across diverse organisms. This review outlines...

Interpretable prediction of neonatal mortality and its key predictors using machine learning and SHAP analysis.

INTRODUCTION: Neonatal mortality is still a global public health concern, especially in lower- and middle-income countries like Ethiopia. Machine lear...

Evaluating Postpartum Hemorrhage Transfusion Risk with a Machine Learning Model for Informed Consent: Retrospective Cohort Study.

BACKGROUND: Postpartum hemorrhage requiring a blood transfusion is a concern for patients and clinicians. Postpartum hemorrhage risk and mode of deliv...

Meta-Learning as a Promising Strategy for Lipid Nanoparticle Optimization and Ionizable Lipid Discovery.

The rapid growth of lipid nanoparticle (LNP)-based RNA therapeutics demands predictive tools to accelerate formulation and lipid design, yet developme...

AI-guided redesign of laboratory-evolved reverse transcriptases enhances prime editing.

Although protein engineering and laboratory evolution have been used to optimize prime editors, we show that previous changes that improve prime edito...

Innovations in pediatric imaging: a scoping review of the past decade with case illustrations.

BACKGROUND: Imaging plays a fundamental and increasing role in the diagnostic work-up of pediatric patients. Non-invasive imaging methods include ultr...

Integrated metabolic and inflammatory biomarkers for early association and prediction of adverse pregnancy outcomes: a multicenter validation study.

BACKGROUND: Adverse pregnancy outcomes (APOs) affect long-term maternal and offspring health. Conventional metabolic markers, including the triglyceri...

Current Documentation in the Delivery Room and Strategies for Improvement.

BACKGROUND: Current neonatal resuscitation program standards recommend the use of real-time documentation completed by a designated scribe. Accurate d...

Comparing the performance of statistical and machine learning survival models in predicting timing and determinants of postnatal care in Rwanda.

BACKGROUND: Postnatal care (PNC) remains the least utilized component of the maternal care continuum despite its critical role in preventing maternal ...