Pregnancy

Deep learning radiomics based on ultrasound images for the assisted diagnosis of chronic kidney disease.

AIM: This study aimed to explore the value of ultrasound (US) images in chronic kidney disease (CKD) screening by constructing a CKD screening model based on grey-scale US images.

Machine learning of Raman spectra predicts drug release from polysaccharide coatings for targeted colonic delivery.

Colonic drug delivery offers numerous pharmaceutical opportunities, including direct access to local therapeutic targets and drug bioavailability benefits arising from the colonic epithelium's reduced abundance of cytochrome P450 enzymes and particular efflux transporters. Current workflows for developing colonic drug delivery systems involve time-consuming, low throughput in vitro and in vivo scr...

Automated Method for Growing Rod Length Measurement on Ultrasound Images in Children With Early Onset Scoliosis.

OBJECTIVE: To develop and validate machine learning algorithms to automatically extract the rod length of the magnetically controlled growing rod from...

Deep learning versus manual morphology-based embryo selection in IVF: a randomized, double-blind noninferiority trial.

To assess the value of deep learning in selecting the optimal embryo for in vitro fertilization, a multicenter, randomized, double-blind, noninferiori...

A deep learning approach to identify the fetal head position using transperineal ultrasound during labor.

OBJECTIVES: To develop a deep learning (DL)-model using convolutional neural networks (CNN) to automatically identify the fetal head position at trans...

Reinforced Computer-Aided Framework for Diagnosing Thyroid Cancer.

Thyroid cancer is the most pervasive disease in the endocrine system and is getting extensive attention. The most prevalent method for an early check ...

Deep learning-based computer-aided detection of ultrasound in breast cancer diagnosis: A systematic review and meta-analysis.

PURPOSE: The aim of this meta-analysis was to assess the diagnostic performance of deep learning (DL) and ultrasound in breast cancer diagnosis. Addit...

Deep learning enables accurate soft tissue tendon deformation estimation in vivo via ultrasound imaging.

Image-based deformation estimation is an important tool used in a variety of engineering problems, including crack propagation, fracture, and fatigue ...

Factors affecting biochemical pregnancy loss (BPL) in preimplantation genetic testing for aneuploidy (PGT-A) cycles: machine learning-assisted identification.

PURPOSE: To determine the factors influencing the likelihood of biochemical pregnancy loss (BPL) after transfer of a euploid embryo from preimplantati...

A YOLOX-Based Deep Instance Segmentation Neural Network for Cardiac Anatomical Structures in Fetal Ultrasound Images.

Echocardiography is an essential procedure for the prenatal examination of the fetus for congenital heart disease (CHD). Accurate segmentation of key ...

Pilot study of machine learning for detection of placenta accreta spectrum.

DeepBP: A transformer-based model for identifying blood-brain barrier penetrating peptides with data augmentation using feedback GAN.

INTRODUCTION: The blood-brain barrier (BBB) serves as a critical structural barrier and impedes the entry of most neurotherapeutic drugs into the brai...

Preoperative Prediction of Axillary Lymph Node Metastasis in Patients With Breast Cancer Through Multimodal Deep Learning Based on Ultrasound and Magnetic Resonance Imaging Images.

RATIONALE AND OBJECTIVES: Deep learning can enhance the performance of multimodal image analysis, which is known for its noninvasive attributes and co...

Integrating Deep Learning-Based Dose Distribution Prediction with Bayesian Networks for Decision Support in Radiotherapy for Upper Gastrointestinal Cancer.

PURPOSE: Selecting the better techniques to harbor optimal motion management, either a stereotactic linear accelerator delivery using TrueBeam (TBX) o...

Biorobotic Drug Delivery for Biomedical Applications.

Despite extensive efforts, current drug-delivery systems face biological barriers and difficulties in bench-to-clinical use. Biomedical robotic system...

Magnetic-actuated hydrogel microrobots with multimodal motion and collective behavior.

Magnetic-actuated miniature robots have sparked growing interest owing to their promising potential in biomedical applications, such as noninvasive di...

Predicting recurrent gestational diabetes mellitus using artificial intelligence models: a retrospective cohort study.

BACKGROUND: We aimed to develop novel artificial intelligence (AI) models based on early pregnancy features to forecast the likelihood of recurrent ge...

Self-learning neural network as a prediction model in non-invasive prenatal testing to detect fetal SNVs.

Ultrasound Image Temperature Monitoring Based on a Temporal-Informed Neural Network.

Real-time and accurate temperature monitoring during microwave hyperthermia (MH) remains a critical challenge for ensuring treatment efficacy and pati...

Artificial intelligence assisted ultrasound for the non-invasive prediction of axillary lymph node metastasis in breast cancer.

PURPOSE: A practical noninvasive method is needed to identify lymph node (LN) status in breast cancer patients diagnosed with a suspicious axillary ly...