Latest AI and machine learning research in radiology for healthcare professionals.
This study aimed to assess the prognostic value of medullary total metabolic tumor volume (mTMTV) derived from fluorodeoxyglucose-positron emission tomography/computed tomography ([18F]FDG-PET/CT) compared with conventional PET-derived features and biological/chromosomal abnormalities in patients with newly diagnosed multiple myeloma (NDMM) treated with daratumumab for induction/consolidation and/...
OBJECTIVE: Lumbar spinal stenosis (LSS) is a degenerative spinal condition characterized by the narrowing of the lumbar spinal canal, leading to back pain and disability. MRI remains the gold standard for LSS diagnosis, but diagnostic variability arises due to the lack of standardized imaging criteria. Recent advancements in artificial intelligence, particularly convolutional neural networks (CNNs...
Sleep plays an important role in memory integration. Closed-loop physical stimulation during rapid eye movement (REM) or non-rapid eye movement (NREM)...
BACKGROUND: Tuberculosis remains a major global health challenge, particularly in resource-limited settings where access to expert radiological interp...
Entropy-based analysis is increasingly used in task-based functional magnetic resonance imaging (fMRI) to quantify neural signal complexity and inform...
Distinguishing scans without evidence of dopaminergic deficit (SWEDD) from Parkinson's disease (PD) remains challenging on routine MRI. We extracted 1...
BACKGROUND: This study aimed to develop and validate a fully three-dimensional (3D) convolutional neural network (3D-CNN) for automated detection of t...
PURPOSE OF REVIEW: Central nervous system (CNS) infections remain a major cause of morbidity and mortality worldwide, particularly in children, older ...
BACKGROUND: Cerebral small vessel disease (CSVD) is a leading cause of stroke and dementia and is associated with cardiac and hematological biomarkers...
Accurate early detection of clinically significant prostate cancer is crucial for improving patient outcomes. However, traditional diagnostic methods ...
BACKGROUND: Magnetic resonance imaging (MRI) of breast tissue is often used to definitively diagnose breast cancer due to its high soft-tissue contras...
BACKGROUND: Recent developments in physiological, imaging and digital biomarkers combined with the approval of new disease-modifying drugs against Alz...
OBJECTIVE: Thyroid eye disease (TED) is an autoimmune condition associated with thyroid dysfunction, often presenting with complex and variable orbita...
BACKGROUND: Transthyretin amyloid cardiomyopathy (ATTR-CM) remains substantially underdiagnosed among Black patient populations. When applied to non-i...
Acute respiratory distress syndrome (ARDS) is a heterogeneous clinical syndrome rather than a single disease. Patients who meet the same diagnostic cr...
BACKGROUND This study aimed to evaluate the effect of SnapShot Freeze 2 (SSF2) on reducing pulsation artifacts in coronary artery imaging of patients ...
PURPOSE: In recent years, much research has been conducted on ultrasound diagnosis of breast tumors using convolutional neural networks (CNNs). While ...
Transoral laser microsurgery (TOLMS) is an established organ-preserving treatment for early-stage and selected intermediate-stage laryngeal squamous c...
Hydrogels, possessing biocompatibility and flexibility, are widely used across biomedical and industrial domains, with their concentration serving as ...
OBJECTIVE: Predictive machine learning (ML) models may help reduce radiology appointment no-shows and late cancellations, which disrupt care, reduce o...