Pregnancy

Sonopermeation combined with stroma normalization enables complete cure using nano-immunotherapy in murine breast tumors.

Nano-immunotherapy shows great promise in improving patient outcomes, as seen in advanced triple-negative breast cancer, but it does not cure the disease, with median survival under two years. Therefore, understanding resistance mechanisms and developing strategies to enhance its effectiveness in breast cancer is crucial. A key resistance mechanism is the pronounced desmoplasia in the tumor microe...

Ultrasound-activated piezoelectric biomaterials for cartilage regeneration.

Due to the low density of chondrocytes and limited ability to repair damaged extracellular matrix (ECM) in cartilage, many patients with congenital or acquired craniofacial trauma require filler graft materials to support facial structure, restore function, improve self-confidence, and regain socialization. Ultrasound has the capacity to stimulate piezoelectric materials, converting mechanical ene...

Exploring the potential of cell-free RNA and Pyramid Scene Parsing Network for early preeclampsia screening.

BACKGROUND: Circulating cell-free RNA (cfRNA) is gaining recognition as an effective biomarker for the early detection of preeclampsia (PE). However, ...

Recent advances in cutaneous drug delivery by iontophoresis.

INTRODUCTION: Iontophoresis has been extensively studied for topical and transdermal drug delivery to stimulate the absorption of molecules that would...

Advancing ocular gene therapy: a machine learning approach to enhance delivery, uptake and gene expression.

Ocular gene therapy offers a promising approach for treating various eye diseases, centered on the process of transfection, including delivery, cellul...

Multifaceted profiling of virus-specific CD8 T cells reveals distinct immune signatures against cytomegalovirus infection states during pregnancy.

Anti-cytomegalovirus (CMV) serological testing, including the IgG avidity index (AI), is used to assess CMV infection phases during pregnancy. However...

Using machine learning to investigate the influence of the prenatal chemical exposome on neurodevelopment of young children.

Research investigating the prenatal chemical exposome and child neurodevelopment has typically focused on a limited number of chemical exposures and c...

Predicting the efficacy of microwave ablation of benign thyroid nodules from ultrasound images using deep convolutional neural networks.

BACKGROUND: Thyroid nodules are frequent in clinical settings, and their diagnosis in adults is growing, with some persons experiencing symptoms. Ultr...

Cardiotocography data analysis for foetal health classification using Spatial Bayesian Neural Network Optimized with Dwarf Mongoose Optimizer.

Pregnancy complications require early detection, but traditional Cardiotocography (CTG) analysis is labor-intensive and error-prone. This manuscript p...

An integrated microfluidic and fluorescence platform for probing in vivo neuropharmacology.

Neurotechnologies and genetic tools for dissecting neural circuit functions have advanced rapidly over the past decade although the development of com...

FetDTIAlign: A deep learning framework for affine and deformable registration of fetal brain dMRI.

Diffusion MRI (dMRI) offers unique insights into the microstructure of fetal brain tissue in utero. Longitudinal and cross-sectional studies of fetal ...

Smart MXene-based microrobots for targeted drug delivery and synergistic therapies.

MXenes and their composites exhibit remarkable electrical conductivity, mechanical flexibility, and biocompatibility, making them ideal candidates for...

Development and validation of machine learning models for predicting post-cesarean pain and individualized pain management strategies: a multicenter study.

BACKGROUND: Effective management of postoperative pain remains a significant challenge in obstetric care due to the variability in pain perception and...

Portal dose image prediction using Monte Carlo generated transmission energy fluence maps of dynamic radiotherapy treatment plans: a deep learning approach.

This work aims to develop and investigate the feasibility of a hybrid model combining Monte Carlo (MC) simulations and deep learning (DL) to predict e...

Point-of-care ultrasound in obstetric anesthesia clinical practice.

PURPOSE OF THE REVIEW: Point-of-care ultrasound (POCUS) is increasingly recognized as a valuable tool in obstetric anesthesia. This review synthesizes...

Mother: a maternal online technology for health care dataset.

OBJECTIVES: These data enable the development of both textual and speech based conversational machine learning models that can be used by expectant mo...

Use of Artificial Intelligence and Machine Learning in Critical Care Ultrasound.

This article explores the transformative potential of artificial intelligence (AI) in critical care ultrasound AI technologies, notably deep learning ...

Prediction of Seronegative Hashimoto's thyroiditis using machine learning models based on ultrasound radiomics: a multicenter study.

BACKGROUND: Seronegative Hashimoto's thyroiditis is often underdiagnosed due to the lack of antibody markers. Combining ultrasound radiomics with mach...

Transformer-based deep learning ensemble framework predicts autism spectrum disorder using health administrative and birth registry data.

Early diagnosis and access to resources, support and therapy are critical for improving long-term outcomes for children with autism spectrum disorder ...

Development and Validation of an Algorithm for Segmentation of the Prostate and its Zones from Three-dimensional Transrectal Multiparametric Ultrasound Images.

BACKGROUND AND OBJECTIVE: Multiparametric ultrasound (mpUS) is being investigated as an alternative to magnetic resonance imaging (MRI) for detection ...