Pregnancy

Deep learning assisted sparse array ultrasound imaging.

This study aims to restore grating lobe artifacts and improve the image resolution of sparse array ultrasonography via a deep learning predictive model. A deep learning assisted sparse array was developed using only 64 or 16 channels out of the 128 channels in which the pitch is two or eight times the original array. The deep learning assisted sparse array imaging system was demonstrated on ex viv...

Investigating pulse-echo sound speed estimation in breast ultrasound with deep learning.

Ultrasound is an adjunct tool to mammography that can quickly and safely aid physicians in diagnosing breast abnormalities. Clinical ultrasound often assumes a constant sound speed to form diagnostic B-mode images. However, the components of breast tissue, such as glandular tissue, fat, and lesions, differ in sound speed. Given a constant sound speed assumption, these differences can degrade the q...

Primary omental pregnancy after in vitro fertilization complicated by hemoperitoneum-how to manage it laparoscopically.

OBJECTIVE: To report an uncommon case of primary OP treated laparoscopically. Ectopic pregnancy (EP) is the leading cause of maternal mortality during...

Robots at your doorstep: acceptance of near-future technologies for automated parcel delivery.

The logistics and delivery industry is undergoing a technology-driven transformation, with robotics, drones, and autonomous vehicles expected to play ...

Risk prediction models for postpartum glucose intolerance in women with a history of gestational diabetes mellitus: a scoping review.

OBJECTIVE: The objective of this scoping review was to investigate the effectiveness and limitations of risk prediction models for postpartum glucose ...

Deep learning-based ultrasound auto-segmentation of the prostate with brachytherapy implanted needles.

BACKGROUND: Accurate segmentation of the clinical target volume (CTV) corresponding to the prostate with or without proximal seminal vesicles is requi...

Trimester-specific exposure to triclocarban during pregnancy: Associations with oxidative stress and size at birth.

Triclocarban (TCC) is an extensively used antimicrobial agent that exhibits endocrine disrupt potential, but its effects on fetal growth remain largel...

Developing and scaling up captopril-loaded electrospun ethyl cellulose fibers for sustained-release floating drug delivery.

In this work ethyl cellulose (EC) was used as the matrix polymer and loaded with captopril, with the goal to fabricate electrospun fibers as potential...

Variability between human experts and artificial intelligence in identification of anatomical structures by ultrasound in regional anaesthesia: a framework for evaluation of assistive artificial intelligence.

BACKGROUND: ScanNavAnatomy Peripheral Nerve Block (ScanNav™) is an artificial intelligence (AI)-based device that produces a colour overlay on real-ti...

Transfer learning for accurate fetal organ classification from ultrasound images: a potential tool for maternal healthcare providers.

Ultrasound imaging is commonly used to aid in fetal development. It has the advantage of being real-time, low-cost, non-invasive, and easy to use. How...

Development of a novel combined nomogram model integrating deep learning radiomics to diagnose IgA nephropathy clinically.

This study aimed to develop and validate a combined nomogram model based on superb microvascular imaging (SMI)-based deep learning (DL), radiomics cha...

Novel Solution for Using Neural Networks for Kidney Boundary Extraction in 2D Ultrasound Data.

: Kidney ultrasound (US) imaging is a significant imaging modality for evaluating kidney health and is essential for diagnosis, treatment, surgical in...

Deep Learning Model Based on Multisequence MRI Images for Assessing Adverse Pregnancy Outcome in Placenta Accreta.

BACKGROUND: Preoperative assessment of adverse outcomes risk in placenta accreta spectrum (PAS) disorders is of high clinical relevance for perioperat...

Interpretable Predictive Models to Understand Risk Factors for Maternal and Fetal Outcomes.

Although most pregnancies result in a good outcome, complications are not uncommon and can be associated with serious implications for mothers and bab...

A multimodal deep learning model for predicting severe hemorrhage in placenta previa.

Placenta previa causes life-threatening bleeding and accurate prediction of severe hemorrhage leads to risk stratification and optimum allocation of i...

Evaluation of the cytotoxic effect of titanium dioxide nanoparticles in human embryonic lung cells.

BACKGROUND/AIM: Titanium dioxide nanoparticles are widely used in a variety of products, including sunscreens, paints, and ceramics. However, their in...

The Promises and Possibilities of Artificial Intelligence in the Delivery of Behavior Analytic Services.

Artificial intelligence (AI) has begun to affect nearly every aspect of our daily lives and nearly every industry and profession. Many readers of this...

Optimal view detection for ultrasound-guided supraclavicular block using deep learning approaches.

Successful ultrasound-guided supraclavicular block (SCB) requires the understanding of sonoanatomy and identification of the optimal view. Segmentatio...

Deep learning for estimation of fetal weight throughout the pregnancy from fetal abdominal ultrasound.

BACKGROUND: Fetal weight is currently estimated from fetal biometry parameters using heuristic mathematical formulas. Fetal biometry requires measurem...

Predicting individual cases of major adolescent psychiatric conditions with artificial intelligence.

Three-quarters of lifetime mental illness occurs by the age of 24, but relatively little is known about how to robustly identify youth at risk to targ...