Radiology

Artificial intelligence in medicine: a scoping review of the risk of deskilling and loss of expertise among physicians.

BACKGROUND: Artificial intelligence (AI) systems are increasingly deployed in clinical practice, par...

Reliability of Rectus Femoris Ultrasound Measurements and Relationship With Truncal Muscle Mass in Healthy Individuals Using Concurrent CT Measurements as the Reference Standard: A Pilot Study.

In chronic diseases, accelerated muscle mass loss is associated with poor clinical outcomes. Compute...

Cross-sectional evaluation of cardiovascular biological age using point-of-care ultrasound.

AIMS: Biological age is increasingly recognized as a superior predictor of morbidity, mortality, com...

Interactive Deep Learning for Myocardial Scar Segmentation Using Cardiovascular Magnetic Resonance.

BACKGROUND: Following myocardial infarction, late gadolinium-enhancement (LGE) assessed by cardiovas...

Comparing large language models and human experts in interpreting MRI reports for personalized patient education.

RATIONALE AND OBJECTIVES: Knee osteoarthritis (OA) is a prevalent global condition. While MRI guides...

AI-based triage and decision support in mammography and digital tomosynthesis for breast cancer screening: a paired, noninferiority trial.

Artificial intelligence (AI) systems have been demonstrated to improve the accuracy of screening mam...

Real-world unified denoising for multi-organ fast MRI: a large-scale prospective validation.

Lengthy acquisition time remains a key bottleneck for the widespread use of MRI in clinics. While ac...

A Deep Learning Framework for Enhanced Ovarian Adnexal Mass Classification Using Routinely Acquired Ultrasound Images.

Accurate classification of ovarian masses is crucial for clinical decision-making. B-mode ultrasound...

Prediction of coronary artery disease using retinal optical coherence tomography angiography imaging and electronic health records: a multimodal machine learning approach.

Improved BG-PVS Quantification in Infant Brain MRI Using Anatomy-Informed Pseudo-Labels for Joint BG and PVS Segmentation.

BACKGROUND: Reliable quantification of perivascular spaces (PVS) in the basal ganglia (BG) is of gro...

Percutaneous coronary intervention in high bleeding risk patients: a review of contemporary management strategies.

INTRODUCTION: High bleeding risk (HBR) affects over one-third of patients undergoing percutaneous co...

BWS-Net: An Optimal Deep Learning Architecture for the Anterior Bladder Wall Segmentation using Ultrasound Imaging.

Urodynamic tests are used to assess bladder function by measuring detrusor pressure, which requires ...

Interpretable Clinical-Radiomics Model for Prediction of Blood Stasis and Left Atrial Appendage Thrombus.

BACKGROUND: The left atrial (LA) morphological profile, anatomically contiguous with the left atrial...

Detecting Distant Metastases in Prostate Cancer Using Whole-body MR Imaging Together with DWIBS (Diffusion-weighted Imaging with Background Body Signal Suppression).

Whole-body MRI (WB-MRI) has evolved over the past 2 decades as a noninvasive imaging technique for d...

MR ProGradeNet A Multi-Resolution Deep Learning Framework for Automated Prostate Cancer Grading from MRI.

Prostate cancer remains a leading cause of cancer-related morbidity in men, and its accurate aggress...

SEQUAL: Self-refining and effective querying active learning with pseudo label divergence score for carotid intima-media segmentation in ultrasound.

Deep learning has achieved remarkable performance in carotid intima-media (CIM) segmentation from ul...

Independent evaluation of deep learning models for detecting focal cortical dysplasia.

The purpose of this study is to perform an independent assessment of three state-of-the-art tools fo...

A multimodal biomechanics dataset with synchronized kinematics and internal tissue motions during reaching.

Tissue motions within body segments, such as the relative movements of muscles, fascia, and bone, re...

Multi-plane vision transformer for hemorrhage classification using axial and sagittal MRI data.

Identifying brain hemorrhages from magnetic resonance imaging (MRI) is a critical task for healthcar...

Advanced Prompt Engineering for Large Language Models in Interventional Radiology: Practical Strategies and Future Perspectives.

As large language models (LLMs) become increasingly integrated into clinical workflows, advanced pro...

Artificial-intelligence models vs. radiologists in the detection of clinically significant prostate cancer on mpMRI: a meta-analysis.

OBJECTIVE: Multiparametric magnetic resonance imaging (mpMRI) detects clinically significant prostat...