Radiology

Prediction Models of Polycyclic Aromatic Hydrocarbons in Urban Road Dust via Magnetic Properties, Particle Size, and Urban Environmental Features.

This study explores the novel application of artificial neural networks to predict polycyclic aromat...

Artificial intelligence-driven early screening and diagnosis of pancreatic cancer: technical innovations, clinical applications, and precision medicine strategies.

BACKGROUND: Pancreatic cancer is characterized by prolonged subclinical progression, molecular heter...

Computational and machine learning approach for nanoparticle-enhanced bio-heat transport with coupled effects of interparticle spacing and nanoparticles radius.

Targeted delivery of drugs and hyperthermia in cardiovascular disease demand the accurate delivery o...

Clinical evaluation of deep learning accelerated 3D magnetic resonance cholangiopancreatography at 1.5 T and 3 T.

OBJECTIVE: Routine clinical 3D magnetic resonance cholangiopancreatography (MRCP) is typically perfo...

Fluoroscopic image-driven deep learning model for predicting intussusception irreducibility during air enema in children.

BACKGROUND: Accurate identification of irreducible intussusception during air enema is crucial for o...

Evaluating AI-powered instruction on Computed Tomography Angiography (CTA) teaching outcomes: a systematic review and meta-analysis.

OBJECTIVE: To systematically evaluate the effectiveness of AI-assisted teaching in computed tomograp...

Identification and verification of worst-case radiological transport scenarios for Ireland: A simulation-based approach to nuclear emergency preparedness (2011-2024).

This study presents a comprehensive simulation-based assessment of potential transboundary radiologi...

The challenge of bringing advances in sacroiliac joint imaging to the clinic.

PURPOSE OF REVIEW: Recently reported criteria are more stringent for classification of axial spondyl...

Development of an Algorithm to Estimate Fat-Free Mass to Optimize Contrast Injection for Computed Tomography Imaging of the Liver.

OBJECTIVES: Contrast-enhanced computed tomography (CT) is central to liver imaging. Inadequate enhan...

Identifying diagnostic biomarkers in functional motor disorders through multimodal behavioral, neurophysiological, and imaging assessment using explainable machine learning.

BACKGROUND: Functional motor disorders (FMDs) represent a frequent and disabling neurological condit...

Attention-based Multimodal Spatiotemporal Enhanced Interaction Network For Major Depressive Disorder Detection.

Although deep learning models have shown promising results in detecting major depressive disorder (M...

Referenceless Proton Resonance Frequency Thermometry Using Deep Learning with Self-Attention.

Proton resonance frequency (PRF) MR thermometry provides temperature feedback for MR-guided focused ...

Magnetic Resonance Neurography: Evolution, Technical Foundations, and Future Directions.

ABSTRACT: In the past 20 years, magnetic resonance neurography has evolved from an experimental tech...

Assessing osteosarcopenia using automated multi-structure-segmentation and Hounsfield unit-based analysis of lumbar muscles and vertebral bodies on computed tomography.

Sarcopenia and osteoporosis are prevalent age-related conditions that substantially increase the ris...

Machine learning outperforms large language models for survival prediction in advanced hepatocellular carcinoma: a multicenter study.

Accurate prognostic prediction remains a critical unmet need in advanced hepatocellular carcinoma (H...

Imaging of ewing sarcoma: an updated analysis including presenting features, prognostic imaging biomarkers, and treatment response assessment.

Ewing sarcoma is a highly aggressive small round cell sarcoma primarily affecting children and adole...

The impact of scanner domain shift on deep learning performance in medical imaging: an experimental study.

PURPOSE: Medical images acquired using different scanners and protocols can differ substantially in ...

Beyond coronary artery calcium score: can lipoprotein(a) and artificial intelligence-coronary computed tomography angiography unmask 'invisible' residual cardiovascular risk?

The Role of Artificial Intelligence Algorithms in Challenging Diagnostic Cases - Between Potential and Real Clinical Support.

INTRODUCTION: Extranodal natural killer/T-cell lymphoma, nasal type (ENKTL), is a rare EBV-associate...

In-hospital electronic monitoring system approaches to epidemiologic investigation and predictive modeling of contrast-induced acute kidney injury.

Contrast-induced acute kidney injury (CI-AKI), the third most common cause of hospital-acquired kidn...

A novel serum metabolite classifier for identifying Metabolic Dysfunction-Associated Steatotic Liver Disease (MASLD) integrating metabolomics and machine learning.

BACKGROUND: Metabolic dysfunction-associated steatotic liver disease (MASLD) presents a growing glob...