Pregnancy

INSAFEDARE Project: Innovative Applications of Assessment and Assurance of Data and Synthetic Data for Regulatory Decision Support.

Digital health solutions hold promise for enhancing healthcare delivery and patient outcomes, primarily driven by advancements such as machine learning, artificial intelligence, and data science, which enable the development of integrated care systems. Techniques for generating synthetic data from real datasets are highly advanced and continually evolving. This paper aims to present the INSAFEDARE...

Remote Monitoring, AI, Machine Learning and Mobile Ultrasound Integration upon 5G Internet in the Prehospital Care to Support the Golden Hour Principle and Optimize Outcomes in Severe Trauma and Emergency Surgery.

AIM: Feasibility and reliability evaluation of 5G internet networks (5G IN) upon Artificial Intelligence (AI)/Machine Learning (ML), of telemonitoring and mobile ultrasound (m u/s) in an ambulance car (AC)- integrated in the pre-hospital setting (PS)- to support the Golden Hour Principle (GHP) and optimize outcomes in severe trauma (TRS).

Data for AI in Congenital Heart Defects: Systematic Review.

Congenital heart disease (CHD) represents a significant challenge in prenatal care due to low prenatal detection rates. Artificial Intelligence (AI) o...

RoCoSDF: Row-Column Scanned Neural Signed Distance Fields for Freehand 3D Ultrasound Imaging Shape Reconstruction

The reconstruction of high-quality shape geometry is crucial for developing freehand 3D ultrasound imaging. However, the shape reconstruction of mul...

Hybrid Artificial Intelligence Solution Combining Convolutional Neural Network and Analytical Approach Showed Higher Accuracy in A-lines Detection on Lung Ultrasound in Thoracic Surgery Patients Compared with Radiology Resident.

OBJECTIVES: Lung ultrasound reduces the number of chest X-rays after thoracic surgery and thus the radiation. COVID-19 pandemic has accelerated resear...

Advancements in Programmable Lipid Nanoparticles: Exploring the Four-Domain Model for Targeted Drug Delivery

Programmable lipid nanoparticles, or LNPs, represent a breakthrough in the realm of targeted drug delivery, offering precise spatiotemporal control ...

A review of robot-assisted ultrasound examination: Systems and technology.

BACKGROUND: At present, the number and overall level of ultrasound (US) doctors cannot meet the medical needs, and the medical ultrasound robots will ...

Robust CNN Multi-Nested-LSTM Framework with Compound Loss for Patch-based Multi-Push Ultrasound Shear Wave Imaging and Segmentation

Ultrasound Shear Wave Elastography (SWE) is a noteworthy tool for in-vivo noninvasive tissue pathology assessment. State-of-the-art techniques can g...

[Deep Learning-Based Artificial Intelligence Model for Automatic Carotid Plaque Identification].

This study aims at developing a dataset for determining the presence of carotid artery plaques in ultrasound images, composed of 1761 ultrasound image...

Machine Learning in Electronic Health Records: Identifying High-Risk Obstetric Patients Pre and During Labor.

Our goal is to apply artificial intelligence (AI) and statistical analysis to understand the relationship between various factors and outcomes during ...

Black-White Differences in Chronic Stress Exposures to Predict Preterm Birth: Interpretable, Race/Ethnicity-Specific Machine Learning Models.

We developed Multivariate Adaptive Regression Splines (MARS) machine learning models of chronic stressors using the Pregnancy Risk Assessment Monitori...

Machine learning to identify endometrial biomarkers predictive of pregnancy success following artificial insemination in dairy cows†.

The objective was to identify a set of genes whose transcript abundance is predictive of a cow's ability to become pregnant following artificial insem...

The Holy Grail of obstetric ultrasound: can artificial intelligence detect hard-to-identify fetal cardiac anomalies?

Deep Learning Classification of Prostate Cancer on Confidently Labeled Micro-Ultrasound Images.

Micro-ultrasound is a high-resolution ultrasound technology that has recently been introduced as an inexpensive alternative to MRI for prostate cancer...

Ultrasound for Automated Classification of Full-Thickness Rotator Cuff Tendon Tears using Deep Learning.

Rotator cuff tendon tears, the most common shoulder injuries, are typically diagnosed mainly through MRI, but can also be seen on ultrasound (US), a m...

3D probe localization from 2D ultrasound images using an RFF-enhanced deep neural network.

Peripheral nerve blocking (PNB) via ultrasound (US) imaging offers the advantages of non-invasiveness, nonionizing radiation, and real-time visualizat...

A comparison between Deep Learning architectures for the assessment of breast tumor segmentation using VSI ultrasound protocol.

Automatic breast tumor ultrasound segmentation is one of the most critical components in the development of tools for breast cancer diagnosis. Several...

Exploring Random Forest Machine Learning for Fetal Movement Detection using Abdominal Acceleration and Angular Rate Data.

Fetal movement is a commonly monitored indicator of fetal wellbeing with reductions in fetal movement being associated with poor perinatal outcomes. H...

Monitoring of Lung Ultrasound Acquisition using Infrared Sensors and Artificial Intelligence.

Lung diseases contribute significantly to global mortality rates. The conventional diagnostic techniques based on medical imaging used for lung diseas...

Transformer-Based Wavelet-Scalogram Deep Learning for Improved Seizure Pattern Recognition in Post-Hypoxic-Ischemic Fetal Sheep EEG.

Hypoxic-ischemic (HI) events in newborns can trigger seizures, which are highly associated with later neurodevelopmental impairment. The precise detec...