Radiology

Health system learning enables generalist neuroimaging models.

Frontier artificial intelligence (AI) models have advanced rapidly through training on internet-scale public data, yet such systems lack access to private clinical data. Neuroimaging is underrepresented in the public domain due to identifiable facial features within magnetic resonance imaging (MRI) and computed tomography (CT) scans, restricting model performance in clinical medicine. Here we show...

A deep learning algorithm for coronary heart disease prediction based on retinal fundus photographs and optical coherence tomography.

BACKGROUND: Coronary heart disease (CHD) is a major cause of mortality worldwide. This study aimed to develop and validate a multimodal deep learning algorithm using retinal imaging to assist in CHD risk assessment. METHODS: In this retrospective study, we developed a deep learning algorithm that integrates retinal fundus photographs and optical coherence tomography (OCT) images. A clinical nomogr...

Factors contributing to the missed diagnosis of incidental gallbladder cancer (IGBC): an integrated analysis of clinical features and ultrasound radiomics.

BACKGROUND: Incidental gallbladder cancer (IGBC) is often diagnosed only during or after cholecystectomy, and preoperative identification remains chal...

Evaluation of AI developed for rib fracture detection in identifying vertebral fractures on abdominal CT.

PURPOSE: To evaluate the performance of an AI algorithm originally developed for rib fracture detection in identifying vertebral fractures on abdomina...

Knee-specific bone quality assessment for cementless total knee arthroplasty candidate selection: a narrative review.

Cementless total knee arthroplasty (TKA) has regained attention in younger, active, and obese patients, supported by advances in implant design, porou...

Artificial Intelligence in Vascular Surgery: Translating Innovation into Clinical Practice: A Narrative Review.

Artificial intelligence (AI) is rapidly reshaping modern medicine, with expanding applications in vascular surgery ranging from diagnostic imaging and...

Time-dependent radiological risk assessment following a severe NPP accident using Monte Carlo simulation, BEIR VII, and interpretable AI.

Nuclear reactor accidents can result in prolonged radiation exposure with complex and uncertain health consequences. Existing studies often focus on d...

Spatial signal distribution learning for high-resolution 3D system matrix calibration in magnetic particle imaging.

OBJECTIVE: Three-dimensional (3D) high-resolution system matrices (HR-SMs) are essential for high-quality image reconstruction in magnetic particl...

GCL-RCA-Net: an RCA-RemUNet-enhanced graph-contrastive framework for hybrid data-driven and dual-branch physics-guided parallel MRI reconstruction.

OBJECTIVE: Parallel magnetic resonance imaging (pMRI) with Cartesian equispaced undersampling accelerates acquisition but introduces structured aliasi...

Machine learning model based on spontaneous brain activity detected by functional MRI for distinguishing unipolar depression from bipolar disorder.

BACKGROUND: The therapeutic strategies for bipolar disorder (BD) and unipolar depression (UD) are quite different. However, the majority of patients w...

SYNTAX score for assessing coronary artery disease burden and complexity: past, present, and future.

The anatomical synergy between percutaneous coronary intervention with TAXUS and cardiac surgery (SYNTAX) score remains a cornerstone for quantifying ...

Prevalence and burden of coronary artery disease in young adults undergoing clinically indicated coronary CT angiography.

BACKGROUND: The reported prevalence and burden of coronary artery disease in young adults varies markedly in published studies from the 1950s through ...

Integrating 3D Volumetric Segmentation and LLM-Based Classification for csPCa Detection on mpMRI: Multi-Institutional External Validation.

RATIONALE AND OBJECTIVES: To develop and externally validate integrated models combining three-dimensional (3D) volumetric segmentation and large lang...

FMR analysis by machine learning leads to remarkable insights into the magnetic anisotropy of [Formula: see text] thin films.

The traditional approach to analyzing ferromagnetic resonance spectroscopy (FMR) data can produce inconsistent material parameters when measurements a...

Ultrasound assisted persulfate for enhanced degradation of Alizarin Red S with experimental design and AI driven optimization.

This study investigates the enhanced degradation of Alizarin Red S (ARS) from aqueous solutions using an ultrasound-assisted persulfate (PS/US) system...

Machine Learning-Based Privacy Preserving via CT/MRI and Organ Metadata Prediction.

Medical imaging plays a significant role in diagnosis and treatment planning, with significant efforts focused on training machine learning (ML) algor...

Automated high-resolution computed tomography analysis outperforms visual assessment in predicting interstitial lung disease progression in systemic sclerosis.

OBJECTIVES: Progressive interstitial lung disease (ILD) is the leading cause of mortality in systemic sclerosis (SSc). Early recognition of progressio...

A method for early ultrasound classification of developmental dysplasia of the hip in infants: combining YOLOv8-based keypoint detection with radiomics.

This study introduces an innovative method for early ultrasound classification of developmental dysplasia of the hip (DDH) in infants, integrating key...

Deep learning-based treatment decision support framework for multi-vessel coronary artery disease using integrated coronary angiography and clinical data.

BACKGROUND: Treatment selection between percutaneous coronary intervention (PCI) and coronary artery bypass grafting (CABG) for multi-vessel coronary ...

Large language model based simplification of ophthalmological clinical and ancillary results for patient readability.

BACKGROUND: Ophthalmological reports are often written at a complexity level that exceeds the reading ability of many patients. Large language models ...