Radiology

Development of a long-term survival prediction model for patients undergoing invasive coronary angiography using ensemble-based machine learning in time-to-event analysis.

BACKGROUND: Prognosis prediction for high-risk patients undergoing invasive coronary angiography (ICA) is crucial for clinical decision-making. Despite machine learning (ML) advancements, time-to-event survival prediction remains limited. OBJECTIVES: This study developed an ensemble ML model based on survival analysis to predict long-term outcomes in ICA patients. METHODS: A total of 9517 ICA pati...

Functional neuroimaging features for predicting the transition from benign paroxysmal positional vertigo to persistent postural-perceptual dizziness.

ObjectivesBenign paroxysmal positional vertigo (BPPV) is a prevalent triggers of persistent postural-perceptual dizziness (PPPD). The maladaptation of brain function may be one of the pathophysiology in PPPD. This study aims to identify brain functional neuroimaging features and establish prediction models to predict PPPD after BPPV.MethodsThe diagnosis of BPPV and PPPD was based on the criteria e...

CDP-KDNet: Curriculum-Guided Dynamic Pruning and Knowledge Distillation for Resource-Efficient Ultrasound Elastography.

In recent years, convolutional neural network (CNN)-based optical flow models for motion estimation have been applied to radio-frequency (RF) ultrasou...

RFDNet: Robust Frequency-Based Denoising Network for 3D Ultrasound Vascular Imaging Using a Row-Column Addressed Array.

Three-dimensional (3D) ultrasound vascular imaging (UVI) is essential for visualizing complex vascular structures. Row-column addressed (RCA) arrays, ...

From automation to agentic artificial intelligence in laboratory medicine: an opinion of the IFCC Division on Emerging Technologies.

Agentic artificial intelligence (AI) systems are distinguished by their ability to invoke multiple tools, compose command chains, and combine chain-of...

Microscopic Propagator Imaging with diffusion MRI.

Microscopic Propagator Imaging (MPI) is a novel diffusion MRI technique that estimates properties, referred to as indices, of the microscopic propagat...

Application of a virtual imaging framework for investigating a deep learning-based reconstruction method for 3D quantitative photoacoustic computed tomography.

Quantitative photoacoustic computed tomography (qPACT) is a promising imaging modality for estimating physiological parameters such as blood oxygen sa...

Diagnostic accuracy of ¹⁸F-FDG PET/CT radiomics for non-invasive prediction of PD-L1 expression in non-small cell lung cancer: A systematic review and meta-analysis.

To evaluate the diagnostic performance, methodological quality, and clinical feasibility of ¹⁸F-FDG PET/CT-based radiomics machine learning models for...

Dermoscopy-guided high-frequency ultrasound: Principles and applications in dermatology.

Conventional skin imaging modalities are often bulky, expensive, and impractical for routine dermatology practice. There is a need for a portable, mul...

Motion Mitigation Techniques for Abdominal and Cardiac MR Imaging.

MRI of the heart and abdominal organs provides unparalleled soft tissue contrast and quantitative biomarkers, yet remains highly susceptible to physio...

Vision-language models in diagnostic imaging: review of technical advances, clinical validation, and practical deployment.

BACKGROUND: Radiology faces an unprecedented workload crisis, creating demand for AI solutions to enhance efficiency and quality. Vision-language mode...

Cardiovascular pulsing-based ultrasound strain imaging with deep learning using paired proximal and distal strain sequences for liver fibrosis detection: a feasibility study.

Accurate assessment of liver fibrosis in the left liver lobe remains clinically challenging due to motion artifacts that compromise the reliability of...

M44TMD: A multimodal, multi-task deep learning framework for comprehensive assessment of TMD-related abnormalities.

OBJECTIVE: Existing deep learning (DL) approaches for assessing temporomandibular disorders (TMD) are limited by underutilization of magnetic resonanc...

Beyond gas bubbles: AI analysis of the "bubble bed" microenvironment improves diagnosis of infected abdominal collections.

BACKGROUND: Accurate diagnosis of infected intra-abdominal fluid collections (IAFCs) is challenging, as the conventional "gas bubble sign" on computed...

Factors Impacting the Performance of Deep Learning Detection of Pulmonary Emboli.

OBJECTIVE: AI models are increasingly adopted in clinical practice, yet their generalizability outside controlled validation settings remains unclear....

Serum FSTL-1 and AI-assessed muscle parameters in cancer-related malnutrition.

OBJECTIVES: Follistatin-like protein-1 (FSTL-1) is emerging as a myokine linking skeletal and muscle biology. We investigated the relationship between...

Ensemble learning-based radiomics model for predicting radiation-induced temporal lobe injury in nasopharyngeal carcinoma.

PURPOSE: To develop and validate a multimodal ensemble machine learning model integrating multi-sequence magnetic resonance imaging (MRI) radiomics, c...

Creation of Radiology Teaching Content with STELLA-A STandardized Electronic Learning Library and Application Platform.

PURPOSE: Collections of interesting cases are at the heart of radiology education, but efficient saving and sharing of cases has always been a challen...

Augmented intelligence for multimodal virtual biopsy in breast cancer using generative artificial intelligence.

OBJECTIVE: This study aims to propose a multimodal, multi-view deep learning approach for breast cancer virtual biopsy, a non-invasive classification ...

Early Insights Among Emergency Medicine Physicians on Artificial Intelligence: A National, Convenience-sample Survey of the American College of Emergency Physicians.

OBJECTIVES: This study aimed to assess the current utilization of artificial intelligence (AI) tools among emergency physicians, their attitudes towar...