Pregnancy

Improving Nurses' Management of Uterine Tachysystole.

PURPOSE: To evaluate the incidence of uterine tachysystole and determine if nurses' management of tachysystole using an artificial intelligence-enabled clinical decision support (cEFM-aiCDS) alert system alone and in combination with an education module about tachysystole could be improved. STUDY DESIGN METHODS: Phase I involved a pre-post study design comparing the incidence and management of tac...

Divide-and-conquer analysis reveals hidden immune cell influencers across the placenta in preeclampsia.

BACKGROUND: Placenta is a focal point of cellular interactions of maternal and fetal immune systems, fostering immune tolerance essential for a successful pregnancy. However, the mechanisms underlying immune dysregulation in disorders such as preeclampsia remain poorly understood. METHODS: We constructed a multilayered atlas of the human placenta by performing single-cell RNA sequencing across dis...

Smart nanomaterials enabling drug delivery and glucose monitoring for diabetes management.

Diabetes mellitus represents one of the most prevalent chronic diseases worldwide, posing serious challenges to global health and healthcare sustainab...

A multiobjective AI model for LNP engineering enhances tissue-selective mRNA delivery.

Lipid nanoparticle (LNP) delivery of RNA therapeutics is constrained by poor tissue selectivity and off-target toxicity. Most high-throughput screenin...

Image quality improvement of liver ultrasound using unsupervised deep learning.

Chronic liver disease (CLD) and subsequent liver cirrhosis (LC) are common causes of death and healthcare-related socio-economical costs worldwide. Ul...

Opportunities for artificial intelligence and synthetic biology in designing living drug delivery systems.

Advances in artificial intelligence (AI) and synthetic biology are transforming biological research and biotechnology. These fields are for the first ...

Artificial intelligence and machine learning in smart vaginal formulation development.

Vaginal drug delivery in women's health remains underutilized and insufficiently studied, largely due to the complexity and dynamic nature of the vagi...

Educational strategies in prenatal anomaly scanning: teaching, simulation and competence assessment.

INTRODUCTION: Prenatal anomaly scanning is a core component of obstetric care, yet remains highly operator-dependent. Variability in training contribu...

Automated Detection of Pediatric Pneumonia via Clinically Driven AI Analysis of Lung Ultrasound.

Lung ultrasound (LUS) is increasingly utilized for diagnosing pediatric pneumonia due to its bedside accessibility, radiation-free nature, and high di...

The role of large language models in the diagnosis and management of obstetric patients: a pilot feasibility study using simulated obstetric cases.

OBJECTIVE: This feasibility study aimed to assess the potential of freely available large language models (LLMs) to support clinical decision-making i...

Evaluating the usability and practicality of AI-enabled smartphone-based obstetric ultrasound in Sierra Leone: a mixed-methods study.

Biological effects of ultrasonic cavitation in cancer therapy: from physics to mechanobiology.

The therapeutic efficacy of systemic treatments in cancer therapy is invariably limited by the biophysical barriers, including vascular endothelial ba...

Reinventing miRNA cancer therapy through immunomodulation and AI.

Despite the rational therapeutic premise of microRNA (miRNA) replacement or inhibition for cancer treatment, its clinical translation remains signific...

Enhancing genomic prediction for key production traits in chickens through ultrasound phenotyping and multi-model comparative analysis.

BACKGROUND: Growth performance and carcass traits are economically vital in poultry breeding. In Wenchang chickens, reducing excessive abdominal fat r...

CT-guided robotic placement of multiple convective delivery cannulas.

OBJECTIVE: Emerging data indicate that the use of cranial robotics with CT guidance can provide an efficient and effective alternative for the simulta...

From structural complexity to causal representation: A dynamic fractal-attention framework for fine-grained ovarian tumor classification in ultrasound.

Accurate fine-grained classification of ovarian tumors from ultrasound images remains challenging due to speckle noise, boundary ambiguity, structural...

DUSTrack: Semi-automated point tracking in ultrasound videos.

UNLABELLED: Ultrasound technology enables safe, non-invasive imaging of dynamic tissue behavior, making it a valuable tool in medicine, biomechanics, ...

Prediction of Pregnancy-Related Cardiovascular Outcomes Using Electrocardiogram-Based Deep Learning Estimation of Cardiorespiratory Fitness.

BACKGROUND: Peak oxygen consumption (peak VO2), the gold standard measure of cardiorespiratory fitness, may identify women at high risk for pregnancy-...

Rehospitalization in Preterm Infants: Machine Learning Prediction Model & Associated Risk Factors.

BACKGROUND AND OBJECTIVES: Preterm birth is a major global health concern, with preterm infants (PI) at increased risk of morbidity and rehospitalizat...

Deep learning-based multimodal radiopathomics for preoperative prediction of lymph node metastasis in papillary thyroid carcinoma.

Papillary thyroid carcinoma (PTC) exhibits a high incidence and a strong propensity for lymph node metastasis (LNM). Accurate preoperative assessment ...