Pregnancy

Interpretable machine learning-based insights into early-life endocrine disruptor exposure and small vulnerable newborns.

Early-life exposure to endocrine-disrupting chemicals (EDCs) may contribute to small vulnerable newborns, including conditions such as being small for gestational age (SGA) and preterm birth (PTB), yet evidence remains limited. This study, which is based on 739 mother-infant pairs in the Chinese Jiashan Birth Cohort (2016-2018), including 39 SGA and 38 PTB cases, employed interpretable machine lea...

Harnessing the oloid shape in magnetically driven robots to enable high-resolution ultrasound imaging.

Magnetic fields enable remote manipulation of objects and are ideal for medical applications because they pass through human tissue harmlessly. This capability is promising for surgical robots, allowing navigation deeper into the human anatomy and accessing organs beyond the reach of current technologies. However, magnetic manipulation is typically limited to a maximum two-degrees-of-freedom orien...

Predicting Risk for Patent Ductus Arteriosus in the Neonate: A Machine Learning Analysis.

: Patent ductus arteriosus (PDA) is common in newborns, being associated with high morbidity and mortality. While maternal and neonatal conditions are...

Multi-center study: ultrasound-based deep learning features for predicting Ki-67 expression in breast cancer.

Applying deep learning algorithms to mine ultrasound features of breast cancer and construct a machine learning model that accurately predicts Ki-67 e...

Early prediction of intraventricular hemorrhage in very low birth weight infants using deep neural networks with attention in low-resource settings.

Early prediction of intraventricular hemorrhage (IVH) in very low-birthweight infants (VLBWIs) remains challenging because of multifactorial risk fact...

Integrating data mining with transcranial focused ultrasound to refine neuralgia treatment strategies.

BACKGROUND: Neuralgia and other neuropathic pain are difficult to treat owing to their complicated etiology and a wide variety of responses to treatme...

High-resolution ultrasound of the annular pulley system in the toes: sonographic anatomy and pathological cases.

OBJECTIVE: To validate high-frequency ultrasound as a valuable imaging modality in the assessment of the annular pulley system of the toes, describing...

Flip Learning: Weakly supervised erase to segment nodules in breast ultrasound.

Accurate segmentation of nodules in both 2D breast ultrasound (BUS) and 3D automated breast ultrasound (ABUS) is crucial for clinical diagnosis and tr...

Quadrupole Magnetic Tweezers for Precise Cell Transportation.

This research introduces a quadrupole magnetic tweezers which can be used for precise cell transportation by actuating magnetic spherical microrobots....

Multiple Instance Learning-Based Prediction of Blood-Brain Barrier Opening Outcomes Induced by Focused Ultrasound.

OBJECTIVE: Targeted blood-brain barrier (BBB) opening using focused ultrasound (FUS) and micro/nanobubbles is a promising method for brain drug delive...

Thinking Like Sonographers: Human-Centered CNN Models for Gout Diagnosis From Musculoskeletal Ultrasound.

We explore the potential of deep convolutional neural network (CNN) models for differential diagnosis of gout from musculoskeletal ultrasound (MSKUS)....

The Artificial Intelligence-Enhanced Echocardiographic Detection of Congenital Heart Defects in the Fetus: A Mini-Review.

Artificial intelligence (AI) is rapidly gaining attention in radiology and cardiology for accurately diagnosing structural heart disease. In this revi...

Automated Detection of Microcracks Within Second Harmonic Generation Images of Cartilage Using Deep Learning.

Articular cartilage, essential for smooth joint movement, can sustain micrometer-scale microcracks in its collagen network from low-energy impacts pre...

CPPCGM: A Highly Efficient Sequence-Based Tool for Simultaneously Identifying and Generating Cell-Penetrating Peptides.

Cell-penetrating peptides (CPPs) are usually short oligopeptides with 5-30 amino acid residues. CPPs have been proven as important drug delivery vehic...

Predictive modeling of pregnancy outcomes utilizing multiple machine learning techniques for in vitro fertilization-embryo transfer.

OBJECTIVE: This study aims to investigate the influencing factors of pregnancy outcomes during in vitro fertilization and embryo transfer (IVF-ET) pro...

CACTUS: An open dataset and framework for automated Cardiac Assessment and Classification of Ultrasound images using deep transfer learning.

Cardiac ultrasound (US) scanning is one of the most commonly used techniques in cardiology to diagnose the health of the heart and its proper function...

Applications of artificial intelligence in ultrasound imaging for carpal-tunnel syndrome diagnosis: a scoping review.

PURPOSE: The purpose of this scoping review is to analyze the application of artificial intelligence (AI) in ultrasound (US) imaging for diagnosing ca...

Artificial intelligence-large language models (AI-LLMs) for reliable and accurate cardiotocography (CTG) interpretation in obstetric practice.

BACKGROUND: Accurate cardiotocography (CTG) interpretation is vital for the monitoring of fetal well-being during pregnancy and labor. Advanced artifi...

Visualized hysteroscopic artificial intelligence fertility assessment system for endometrial injury: an image-deep-learning study.

OBJECTIVE: Asherman's syndrome (AS) is a significant cause of subfertility in women from developing countries. Over 80% of AS cases in these regions a...

A scoping review on the integration of artificial intelligence in point-of-care ultrasound: Current clinical applications.

BACKGROUND: Artificial intelligence (AI) is used increasingly in point-of-care ultrasound (POCUS). However, the true role, utility, advantages, and li...