Pregnancy

A Computational Predictor for Accurate Identification of Tumor Homing Peptides by Integrating Sequential and Deep BiLSTM Features.

Cancer remains a severe illness, and current research indicates that tumor homing peptides (THPs) pl...

A fully autonomous robotic ultrasound system for thyroid scanning.

The current thyroid ultrasound relies heavily on the experience and skills of the sonographer and th...

Machine learning in prenatal MRI predicts postnatal ventricular abnormalities in fetuses with isolated ventriculomegaly.

OBJECTIVES: To evaluate the intracranial structures and brain parenchyma radiomics surrounding the o...

Branched Convolutional Neural Networks for Receiver Channel Recovery in High-Frame-Rate Sparse-Array Ultrasound Imaging.

For high-frame-rate ultrasound imaging, it remains challenging to implement on compact systems as a ...

Machine Learning to Predict Outcomes of Fetal Cardiac Disease: A Pilot Study.

Prediction of outcomes following a prenatal diagnosis of congenital heart disease (CHD) is challengi...

Engineering mannose-functionalized nanostructured lipid carriers by sequential design using hybrid artificial intelligence tools.

Nanostructured lipid carriers (NLCs) hold significant promise as drug delivery systems (DDS) owing t...

PSFHSP-Net: an efficient lightweight network for identifying pubic symphysis-fetal head standard plane from intrapartum ultrasound images.

The accurate selection of the ultrasound plane for the fetal head and pubic symphysis is critical fo...

Fresh tools, familiar findings: machine learning in prediction of pregnancy loss.

Artificial intelligence-based, semi-automated segmentation for the extraction of ultrasound-derived radiomics features in breast cancer: a prospective multicenter study.

PURPOSE: To investigate the feasibility of an artificial intelligence (AI)-based semi-automated segm...

A Review of Artificial Intelligence in Breast Imaging.

With the increasing dominance of artificial intelligence (AI) techniques, the important prospects fo...

Accuracy of early pregnancy diagnosis and determining pregnancy loss using different biomarkers and machine learning applications in dairy cattle.

This study aimed to compare the accuracy of IFN-τ stimulated gene abundance (ISGs) in peripheral blo...

Use of artificial intelligence in obstetric and gynaecological diagnostics: a protocol for a systematic review and meta-analysis.

INTRODUCTION: Emerging developments in applications of artificial intelligence (AI) in healthcare of...

RSV Severe Infection Risk Stratification in a French 5-Year Birth Cohort Using Machine-learning.

BACKGROUND: Respiratory syncytial virus (RSV) poses a substantial threat to infants, often leading t...

Multimodal radiotherapy dose prediction using a multi-task deep learning model.

BACKGROUND: In radiation therapy (RT), accelerated partial breast irradiation (APBI) has emerged as ...

Enhancing Fetal Electrocardiogram Signal Extraction Accuracy through a CycleGAN Utilizing Combined CNN-BiLSTM Architecture.

The fetal electrocardiogram (FECG) records changes in the graph of fetal cardiac action potential du...

HFSCCD: A Hybrid Neural Network for Fetal Standard Cardiac Cycle Detection in Ultrasound Videos.

In the fetal cardiac ultrasound examination, standard cardiac cycle (SCC) recognition is the essenti...

Improving Needle Tip Tracking and Detection in Ultrasound-Based Navigation System Using Deep Learning-Enabled Approach.

Ultrasound-guided percutaneous interventions have numerous advantages over traditional techniques. A...

How can industrial intelligence change the employment structure of the floating population?

As the wave of industrial intelligence (AI) swept, the demographic dividend era in the Chinese labor...

Toward confident prostate cancer detection using ultrasound: a multi-center study.

PURPOSE: Deep learning-based analysis of micro-ultrasound images to detect cancerous lesions is a pr...

TransEBUS: The interpretation of endobronchial ultrasound image using hybrid transformer for differentiating malignant and benign mediastinal lesions.

The purpose of this study is to establish a deep learning automatic assistance diagnosis system for ...

PSFHS: Intrapartum ultrasound image dataset for AI-based segmentation of pubic symphysis and fetal head.

During the process of labor, the intrapartum transperineal ultrasound examination serves as a valuab...