Radiology

Latest AI and machine learning research in radiology for healthcare professionals.

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Nystagmus in Clinical Practice: From Diagnosis to Treatment-A Comprehensive Review.

Nystagmus, a common yet intricate ocular movement disorder, significantly contributes to visual morb...

Hand and Elbow Nerve Entrapments: MR Imaging Evaluation.

Entrapment neuropathies are the result of compression, displacement, traction, or irritation of peri...

Machine learning-assisted fluorescence/smartphone dual-mode platform for lead ion detection using the novel polyimide covalent organic framework.

Unintended leakage of toxic and lead ion (Pb) ions poses high harmful to human health and environmen...

Dynamic Predictive Models of Cardiogenic Shock in STEMI: Focus on Interventional and Critical Care Phases.

: While early risk stratification in STEMI is essential, the threat of cardiogenic shock (CS) persis...

Optimization of Protein Extraction from Rapeseed Oil Cake by Dephenolization Process for Scale-Up Application Using Artificial Neural Networks.

Rapeseed proteins, due to their quality and wide availability, have great potential for application ...

MRMS-CNNFormer: A Novel Framework for Predicting the Biochemical Recurrence of Prostate Cancer on Multi-Sequence MRI.

Accurate preoperative prediction of biochemical recurrence (BCR) in prostate cancer (PCa) is essenti...

SFPGCL: Specificity-preserving federated population graph contrastive learning for multi-site ASD identification using rs-fMRI data.

Autism spectrum disorder (ASD) is a severe neurodevelopmental disorder that affects people's social ...

Deep learning predicts HER2 status in invasive breast cancer from multimodal ultrasound and MRI.

The preoperative human epidermal growth factor receptor type 2 (HER2) status of breast cancer is typ...

The imaging crisis in axial spondyloarthritis.

Imaging holds a pivotal yet contentious role in the early diagnosis of axial spondyloarthritis. Alth...

FlowMRI-Net: A Generalizable Self-Supervised 4D Flow MRI Reconstruction Network.

BACKGROUND: Image reconstruction from highly undersampled 4D flow MRI data can be very time consumin...

Diagnostic challenges of carpal tunnel syndrome in patients with congenital thenar hypoplasia: a comprehensive review.

Carpal Tunnel Syndrome (CTS) is the most common entrapment neuropathy, frequently presenting with pa...

How early can we detect diabetic retinopathy? A narrative review of imaging tools for structural assessment of the retina.

Despite current screening models, enhanced imaging modalities, and treatment regimens, diabetic reti...

Lightweight hybrid transformers-based dyslexia detection using cross-modality data.

Early and precise diagnosis of dyslexia is crucial for implementing timely intervention to reduce it...

Development and validation of clinical-radiomics deep learning model based on MRI for endometrial cancer molecular subtypes classification.

OBJECTIVES: This study aimed to develop and validate a clinical-radiomics deep learning (DL) model b...

What are the perceptions of AI in radiology among UK medical students and junior doctors?

BackgroundThe integration of artificial intelligence (AI) in radiology has the potential to improve ...

AI-assisted diffuse correlation tomography for identifying breast cancer.

SIGNIFICANCE: Diffuse correlation tomography (DCT) is an emerging technique for the noninvasive meas...

Developing cardiac digital twin populations powered by machine learning provides electrophysiological insights in conduction and repolarization.

Large-cohort imaging and diagnostic studies often assess cardiac function but overlook underlying bi...

"MR Fingerprinting for Imaging Brain Hemodynamics and Oxygenation".

Over the past decade, several studies have explored the potential of magnetic resonance fingerprinti...

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