Pregnancy

Using Deep Learning in a Monocentric Study to Characterize Maternal Immune Environment for Predicting Pregnancy Outcomes in the Recurrent Reproductive Failure Patients.

Recurrent reproductive failure (RRF), such as recurrent pregnancy loss and repeated implantation failure, is characterized by complex etiologies and particularly associated with diverse maternal factors. It is currently believed that RRF is closely associated with the maternal environment, which is, in turn, affected by complex immune factors. Without the use of automated tools, it is often diffic...

Ultra-high-frequency ultrasound and machine learning approaches for the differential diagnosis of melanocytic lesions.

Malignant melanoma (MM) is one of the most dangerous skin cancers. The aim of this study was to present a potential new method for the differential diagnosis of MM from melanocytic naevi (MN). We examined 20 MM and 19 MN with a new ultra-high-frequency ultrasound (UHFUS) equipped with a 70 MHz linear probe. Ultrasonographic images were processed for calculating 8 morphological parameters (area, pe...

Intravascular ultrasound-based deep learning for plaque characterization in coronary artery disease.

BACKGROUND AND AIMS: Although plaque characterization by intravascular ultrasound (IVUS) is important for risk stratification, frame-by-frame analysis...

Image Quality Enhancement Using a Deep Neural Network for Plane Wave Medical Ultrasound Imaging.

Plane wave imaging (PWI), a typical ultrafast medical ultrasound imaging mode, adopts single plane wave emission without focusing to achieve a high fr...

Machine learning analysis of pregnancy data enables early identification of a subpopulation of newborns with ASD.

To identify newborns at risk of developing ASD and to detect ASD biomarkers early after birth, we compared retrospectively ultrasound and biological m...

One-shot object parsing in newborn chicks.

Controlled-rearing studies provide the unique opportunity to examine which psychological mechanisms are present at birth and which mechanisms emerge f...

Stakeholders' views on the organisational factors affecting application of artificial intelligence in healthcare: a scoping review protocol.

INTRODUCTION: Artificial intelligence (AI) offers great potential for transforming healthcare delivery leading to better patient-outcomes and more eff...

Imbalanced Loss-Integrated Deep-Learning-Based Ultrasound Image Analysis for Diagnosis of Rotator-Cuff Tear.

A rotator cuff tear (RCT) is an injury in adults that causes difficulty in moving, weakness, and pain. Only limited diagnostic tools such as magnetic ...

Assessment of Collaborative Robot (Cobot)-Assisted Histotripsy for Venous Clot Ablation.

OBJECTIVE: The application of bubble-based ablation with the focus ultrasound therapy histotripsy is gaining traction for the treatment of venous thro...

Machine learning to determine optimal conditions for controlling the size of elastin-based particles.

This paper evaluates the aggregation behavior of a potential drug and gene delivery system that combines branched polyethyleneimine (PEI), a positivel...

Deep learning-based intravascular ultrasound segmentation for the assessment of coronary artery disease.

BACKGROUND: Accurate segmentation of the coronary arteries with intravascular ultrasound (IVUS) is important to optimize coronary stent implantation. ...

Proposing a machine-learning based method to predict stillbirth before and during delivery and ranking the features: nationwide retrospective cross-sectional study.

BACKGROUND: Stillbirth is defined as fetal loss in pregnancy beyond 28 weeks by WHO. In this study, a machine-learning based method is proposed to pre...

Detection of prenatal alcohol exposure using machine learning classification of resting-state functional network connectivity data.

Fetal Alcohol Spectrum Disorder (FASD), a wide range of physical and neurobehavioral abnormalities associated with prenatal alcohol exposure (PAE), is...

The evolving role of EUS-guided tissue acquisition.

The introduction of endoscopic ultrasound-guided fine-needle aspiration into clinical practice was a pivotal moment for diagnostic gastrointestinal en...

The ameliorating approach of nanorobotics in the novel drug delivery systems: a mechanistic review.

Nanoscale robotics have the ability that it can productively transform multiple energy sources into motion and strength which reflects an expeditiousl...

Automatic deep learning-based pleural effusion classification in lung ultrasound images for respiratory pathology diagnosis.

Lung ultrasound (LUS) imaging as a point-of-care diagnostic tool for lung pathologies has been proven superior to X-ray and comparable to CT, enabling...

GestAltNet: aggregation and attention to improve deep learning of gestational age from placental whole-slide images.

The placenta is the first organ to form and performs the functions of the lung, gut, kidney, and endocrine systems. Abnormalities in the placenta caus...

Development of a convolutional neural network to differentiate among the etiology of similar appearing pathological B lines on lung ultrasound: a deep learning study.

OBJECTIVES: Lung ultrasound (LUS) is a portable, low-cost respiratory imaging tool but is challenged by user dependence and lack of diagnostic specifi...

Artificial intelligence for breast ultrasound: An adjunct tool to reduce excessive lesion biopsy.

PURPOSE: To determine whether adding an artificial intelligence (AI) system to breast ultrasound (US) can reduce unnecessary biopsies.

Prediction of newborn's body mass index using nationwide multicenter ultrasound data: a machine-learning study.

BACKGROUND: This study introduced machine learning approaches to predict newborn's body mass index (BMI) based on ultrasound measures and maternal/del...