Pregnancy

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 ...

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, wh...

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 ...

Automatic diagnosis for adenomyosis in ultrasound images by deep neural networks.

OBJECTIVE: To present a new noninvasive technique for automatic diagnosis of adenomyosis, using a no...

Biorobotic Drug Delivery for Biomedical Applications.

Despite extensive efforts, current drug-delivery systems face biological barriers and difficulties i...

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

Magnetic-actuated miniature robots have sparked growing interest owing to their promising potential ...

Sound of synergy: ultrasound and artificial intelligence in sports medicine.

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 f...

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

Real-time and accurate temperature monitoring during microwave hyperthermia (MH) remains a critical ...

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

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 cance...

Interpretable machine learning models for predicting clinical pregnancies associated with surgical sperm retrieval from testes of different etiologies: a retrospective study.

BACKGROUND: The relationship between surgical sperm retrieval of different etiologies and clinical p...

Deep learning model based on contrast-enhanced ultrasound for predicting vessels encapsulating tumor clusters in hepatocellular carcinoma.

OBJECTIVES: To establish and validate a non-invasive deep learning (DL) model based on contrast-enha...

Ultrasound-based deep learning radiomics nomogram for differentiating mass mastitis from invasive breast cancer.

BACKGROUND: The purpose of this study is to develop and validate the potential value of the deep lea...

AGILE platform: a deep learning powered approach to accelerate LNP development for mRNA delivery.

Ionizable lipid nanoparticles (LNPs) are seeing widespread use in mRNA delivery, notably in SARS-CoV...

A deep learning-based method for the detection and segmentation of breast masses in ultrasound images.

Automated detection and segmentation of breast masses in ultrasound images are critical for breast c...

Automatic robotic doppler sonography of leg arteries.

PURPOSE: Robot-assisted systems offer an opportunity to support the diagnostic and therapeutic treat...

ChatGPT and dermatology.

Since the development of the artificial intelligence (AI), several applications have been proposed. ...

Deep learning based detection and classification of fetal lip in ultrasound images.

OBJECTIVES: Fetal cleft lip is a common congenital defect. Considering the delicacy and difficulty o...

Endobronchial Ultrasound-Based Support Vector Machine Model for Differentiating between Benign and Malignant Mediastinal and Hilar Lymph Nodes.

INTRODUCTION: The aim of the study was to establish an ultrasonographic radiomics machine learning m...