Pregnancy

Engineered multi-domain lipid nanoparticles for targeted delivery.

Engineered lipid nanoparticles (LNPs) represent a breakthrough in targeted drug delivery, enabling precise spatiotemporal control essential to treat complex diseases such as cancer and genetic disorders. However, the complexity of the delivery process-spanning diverse targeting strategies and biological barriers-poses significant challenges to optimizing their design. To address these, this review...

Can automation and artificial intelligence reduce echocardiography scan time and ultrasound system interaction?

BACKGROUND: The number of patients referred for and requiring a transthoracic echocardiogram (TTE) has increased over the years resulting in more cardiac sonographers reporting work related musculoskeletal pain. We sought to determine if a scanning protocol that replaced conventional workflows with advanced technologies such as multiplane imaging, artificial intelligence (AI) and automation could ...

Low birth weight among neonates: Investigating incidence, risk factors, and AI-enabled predictive modeling for risk estimation.

BackgroundLow birth weight serves as a vital measure of maternal health and the efficacy of prenatal care globally. The study was aimed to assess the ...

Predicting mucosal healing in Crohn's disease: development of a deep-learning model based on intestinal ultrasound images.

OBJECTIVE: Predicting treatment response in Crohn's disease (CD) is essential for making an optimal therapeutic regimen, but relevant models are lacki...

A Semi-supervised Ultrasound Image Segmentation Network Integrating Enhanced Mask Learning and Dynamic Temperature-controlled Self-distillation.

Ultrasound imaging is widely used in clinical practice due to its advantages of no radiation and real-time capability. However, its image quality is o...

Whole-lesion-aware network based on freehand ultrasound video for breast cancer assessment: a prospective multicenter study.

BACKGROUND: The clinical application of artificial intelligence (AI) models based on breast ultrasound static images has been hindered in real-world w...

NanoBinder: a machine learning assisted nanobody binding prediction tool using Rosetta energy scores.

Nanobodies offer significant therapeutic potential due to their small size, stability, and versatility. Although advancements in computational protein...

The Future of Automated Insulin Delivery Systems.

Automated insulin delivery (AID) systems have revolutionized diabetes care by integrating continuous glucose monitoring (CGM), insulin pumps, and adva...

Application Value of Deep Learning-Based AI Model in the Classification of Breast Nodules.

Breast nodules are highly prevalent among women, and ultrasound is a widely used screening tool. However, single ultrasound examinations often result...

ThreeF-Net: Fine-grained feature fusion network for breast ultrasound image segmentation.

Convolutional Neural Networks (CNNs) have achieved remarkable success in breast ultrasound image segmentation, but they still face several challenges ...

Enhancing Free-hand 3D Photoacoustic and Ultrasound Reconstruction using Deep Learning.

This study introduces a motion-based learning network with a global-local self-attention module (MoGLo-Net) to enhance 3D reconstruction in handheld p...

Uncovering ethical biases in publicly available fetal ultrasound datasets.

We explore biases present in publicly available fetal ultrasound (US) imaging datasets, currently at the disposal of researchers to train deep learnin...

Current status and challenges of minimally invasive ultrasound thermal ablation technology.

Image-guided minimally invasive ultrasound thermal ablation has been widely studied for disease treatment due to its unique advantages, such as large ...

OneTouch Automated Photoacoustic and Ultrasound Imaging of Breast in Standing Pose.

We developed an automated photoacoustic and ultrasound breast tomography system that images the patient in the standing pose. The system, named OneTou...

3D Quantification of Viral Transduction Efficiency in Living Human Retinal Organoids.

The development of therapeutics builds on testing their efficiency in vitro. To optimize gene therapies, for example, fluorescent reporters expressed ...

Exploring the limit of image resolution for human expert classification of vascular ultrasound images in giant cell arteritis and healthy subjects: the GCA-US-AI project.

OBJECTIVES: Prompt diagnosis of giant cell arteritis (GCA) with ultrasound is crucial for preventing severe ocular and other complications, yet expert...

Current and emerging strategies for subcutaneous delivery of high-concentration and high-dose antibody therapeutics.

Subcutaneous (SC) administration of monoclonal antibodies (mAbs) offers patient-centric benefits such as self-administration, fewer hospital visits, a...

Air Pollution and Autism Spectrum Disorder: Unveiling Multipollutant Risks and Sociodemographic Influences in California.

BACKGROUND: Autism spectrum disorder (ASD) is a neurodevelopmental condition with increasing prevalence worldwide. Air pollution may be a major contri...

In situ foliar augmentation of multiple species for optical phenotyping and bioengineering using soft robotics.

Precision agriculture aims to increase crop yield while reducing the use of harmful chemicals, such as pesticides and excess fertilizer, using minimal...

Preventive and therapeutic strategies via health care delivery system to minimize sight-threatening diabetic retinopathy: a narrative review.

PURPOSE OF REVIEW: To highlight various preventive and therapeutic strategies via health care delivery system to minimize sight-threatening diabetic r...