Radiology

[Application of artificial intelligence to pharmacological and interventional treatment].

As in many other fields, artificial intelligence (AI) is transforming daily activities in cardiology...

Predicting ventilation from single breathing phase non-contrast CT using Swin Transformers.

BACKGROUND: Pulmonary ventilation imaging enables functional avoidance radiotherapy treatment plans ...

Feasibility of Free-breathing Deep Learning-reconstructed Single-Shot Cine MRI in Participants with Arrhythmia: Comparison with Conventional Segmented Cine MRI.

Purpose To evaluate the feasibility of retrospective electrocardiographically (ECG) gated single-sho...

ICECREAM: high-fidelity equivariant cryo-electron tomography.

Cryo-electron tomography (cryo-ET) visualizes 3D cellular architecture in its near-native state. The...

Deep Learning for Automated Tumor Segmentation of Rectal Cancer on T2-Weighted Magnetic Resonance Images.

PURPOSE: To develop a deep learning (DL)-based automated segmentation model for rectal cancer on T2-...

Retrieval-Augmented Language Models for Patient-Centered Periprocedural Anticoagulation in Interventional Radiology.

PURPOSE: This study evaluates Large Language Models (LLMs) integrated with Retrieval-Augmented Gener...

Large Language Models in Clinical Decision Support: A Comparative Analysis of Chat-GPT and Breast Radiologists on ACR Appropriateness Criteria.

RATIONALE AND OBJECTIVES: This study evaluates the performance of ChatGPT, a large language model (L...

Automating the segmentation, date extraction, and classification of multi-report PDFs in outside medical records using optical character recognition and generative artificial intelligence.

OBJECTIVES: Patients referred for specialized care often arrive with outside medical records (OMRs) ...

Efficient denoising in LED-based optoacoustic tomography with squeeze-and-excitation deep convolutional networks.

SIGNIFICANCE: Low-cost optoacoustic imaging based on light-emitting diodes (LEDs) offers an affordab...

Pre-heart failure in early chronic kidney disease: clinical epidemiology and treatment.

Chronic kidney disease (CKD), defined per the Kidney Disease: Improving Global Outcomes (KDIGO) guid...

Artificial Intelligence-Assisted Ultrasound in Austere Trauma Environments: Implications for Role 1 Military Medicine.

Pararescue jumpers are United States Air Force medical tactical operators who provide advanced traum...

KidMesh: Computational Mesh Reconstruction for Pediatric Congenital Hydronephrosis Using Deep Neural Networks.

Pediatric congenital hydronephrosis (CH) is a common urinary tract disorder, primarily caused by obs...

Automatic Detection of Multiple Artifacts in Computed Tomography Images by Self-Attention Guided Vision Transformer.

Automated detection of image artifacts is crucial for enhancing the efficiency and quality of comput...

Robotics in Interventional Oncology: A Call to Arms?

Integrating multi-omics data and artificial intelligence for personalized medicine in glioblastoma.

Glioblastoma (GBM) is one of the most lethal primary brain tumors and is characterized by profound m...

Review of agentic artificial intelligence (AI) in radiology: from current clinical integration to future innovations.

AIM: Artificial intelligence (AI) is one of the most revolutionary developments in the field of medi...

Artificial Intelligence-Enhanced Cardiac Point-of-Care Ultrasound: A Prospective Single-Arm Study.

OBJECTIVE: To evaluate the clinical utility of combining artificial intelligence (AI) with handheld ...

The oral-gut microbiome axis in diabetes mellitus: a systematic review and emerging clinical perspectives.

Emerging evidence suggests that diabetes mellitus (DM) is not only a metabolic disorder but also a m...

Artificial Intelligence as an Add-On Instrument in Fetal Ultrasound; Sonographers' and Obstetricians' Expectations.

OBJECTIVE: Artificial intelligence applications (AIA) in fetal ultrasound are rapidly evolving, yet ...

Transformer-based super-resolution lung CT images improve visualization of multiple diseases.

OBJECTIVES: To assess the Transformer-based Swin2SR model for super-resolution (SR) enhancement of l...

Artificial Intelligence prognostication of liver disease using imaging.

Accurate prognostic tools in patients with chronic liver disease (CLD) have the potential to improve...