Pregnancy

Update on the detection of frailty in older adults: a multicenter cohort machine learning-based study protocol.

BACKGROUND: This study aims to investigate the relationship between muscle activation variables assessed via ultrasound and the comprehensive assessment of geriatric patients, as well as to analyze ultrasound images to determine their correlation with morbimortality factors in frail patients.

How might the rapid development of artificial intelligence affect the delivery of UK Defence healthcare?

Artificial intelligence (AI) has developed greatly and is now at the centre of technological advancements. Current and recent military conflicts have highlighted the evolving complexity of warfare with rapid technological change at the heart of it. AI aims to understand and design systems that show signs of intelligence and are able to learn by deriving knowledge from data. There have been multipl...

Deep learning classification integrating embryo images with associated clinical information from ART cycles.

An advanced Artificial Intelligence (AI) model that leverages cutting-edge computer vision techniques to analyse embryo images and clinical data, enab...

Explicating the transformative role of artificial intelligence in designing targeted nanomedicine.

INTRODUCTION: Artificial intelligence (AI) has emerged as a transformative force in nanomedicine, revolutionizing drug delivery, diagnostics, and pers...

Automated Fetal Biometry Assessment with Deep Ensembles using Sparse-Sampling of 2D Intrapartum Ultrasound Images

The International Society of Ultrasound advocates Intrapartum Ultrasound (US) Imaging in Obstetrics and Gynecology (ISUOG) to monitor labour progres...

Blind Restoration of High-Resolution Ultrasound Video

Ultrasound imaging is widely applied in clinical practice, yet ultrasound videos often suffer from low signal-to-noise ratios (SNR) and limited reso...

Evaluating Prevalence of Preterm Postnatal Growth Faltering Using Fenton 2013 and INTERGROWTH-21st Growth Charts with Logistic and Machine Learning Models.

Postnatal growth faltering (PGF) significantly affects premature neonates, leading to compromised neurodevelopment and an increased risk of long-term...

An explainable AI-driven deep neural network for accurate breast cancer detection from histopathological and ultrasound images.

Breast cancer represents a significant global health challenge, which makes it essential to detect breast cancer early and accurately to improve patie...

A Skull-Adaptive Framework for AI-Based 3D Transcranial Focused Ultrasound Simulation

Transcranial focused ultrasound (tFUS) is an emerging modality for non-invasive brain stimulation and therapeutic intervention, offering millimeter-...

Machine-Learning Framework to Predict the Performance of Lipid Nanoparticles for Nucleic Acid Delivery.

Lipid nanoparticles (LNPs) are highly effective carriers for gene therapies, including mRNA and siRNA delivery, due to their ability to transport nucl...

Machine learning based clinical decision tool to predict acute kidney injury and survival in therapeutic hypothermia treated neonates.

Therapeutic hypothermia (TH) significantly reduces mortality and morbidities in neonates with Neonatal Encephalopathy (NE). NE may result in neonatal ...

OpenPros: A Large-Scale Dataset for Limited View Prostate Ultrasound Computed Tomography

Prostate cancer is one of the most common and lethal cancers among men, making its early detection critically important. Although ultrasound imaging...

Patient-Specific Autoregressive Models for Organ Motion Prediction in Radiotherapy

Radiotherapy often involves a prolonged treatment period. During this time, patients may experience organ motion due to breathing and other physiolo...

Assessing fetal lung maturity: Integration of ultrasound radiomics and deep learning.

This study built a model to forecast the maturity of lungs by blending radiomics and deep learning methods. We examined ultrasound images from 263 pre...

Computer-aided assessment for enlarged fetal heart with deep learning model.

Enlarged fetal heart conditions may indicate congenital heart diseases or other complications, making early detection through prenatal ultrasound esse...

Unlocking the secrets: Structure-function dynamics of plant proteins.

Plant-based proteins are becoming essential resources for sustainable food systems, pharmaceutical innovations, and functional materials. This review ...

Early Detection of Fetal Health Conditions Using Machine Learning for Classifying Imbalanced Cardiotocographic Data.

Cardiotocography (CTG) is widely used in obstetrics to monitor fetal heart rate and uterine contractions. It helps detect early signs of fetal distre...

Integrating ultrasound and serum indicators for evaluating outcomes of targeted immunotherapy in advanced liver cancer.

BACKGROUND: Hepatocellular carcinoma (HCC) is a major global contributor to cancer-related mortality, with advanced stages presenting substantial ther...

Segmentation of the thoracolumbar fascia in ultrasound imaging: a deep learning approach.

BACKGROUND: Only in recent years it has been demonstrated that the thoracolumbar fascia is involved in low back pain (LBP), thus highlighting its impl...

Effects of neonicotinoid pesticide exposure in the first trimester on gestational diabetes mellitus based on interpretable machine learning.

BACKGROUND: Gestational diabetes mellitus (GDM) is one of the most common pregnancy complications and seriously threatens the health of mothers and of...