Latest AI and machine learning research in neurology for healthcare professionals.
PURPOSE: MRI detection of subtle focal cortical dysplasia (FCD)-like abnormalities remains challenging in focal epilepsy. Higher signal-to-noise ratio and spatial resolution offered by ultra-high-field 7T MRI and surface-based graph-neural-network (GNN) analysis may improve detection of subtle cortical abnormalities. We evaluated whether combining 7T MRI with a surface-based GNN classifier improve...
PURPOSE: Scoliosis (a spinal ailment) with improper lateral curvature and rotational abnormalities may have a significant impact on the general health and physical development of a person. For thediagnosis of this problem, Cobb angle measurement is required from Anterior-Posterior (AP) X-ray images. At present, a manual estimate is performed, which is time-consuming and prone to error.Usingthis du...
Deep learning (DL) methods increasingly outperform classical approaches in brain MRI analysis, yet their generalizability across independent imaging c...
INTRODUCTION: Falls in older adults with dementia are common and have multiple consequences for their health and quality of life. Fall prediction mode...
Multi-modal models that fuse neuroimaging with clinical assessment data represent the current state of the art for automated Alzheimer's disease detec...
Motor neuron diseases (MNDs) are caused by the progressive loss of motor neurons and eventually lead to paralysis and death. Once viewed as primarily ...
BACKGROUND: GM1 gangliosidosis is an inherited, progressive, and fatal neurodegenerative lysosomal storage disorder with no approved treatment. In thi...
Although some drugs have been approved for clinical treatment, early diagnosis and intervention remain the most effective strategies for managing Alzh...
PURPOSE: Cognitive motor dissociation (CMD) is associated with long-term recovery in acute brain injury, but CMD testing is only available in few cent...
OBJECTIVES: Deep-learning (DL)-accelerated MRI can significantly reduce acquisition times. Studies evaluating interchangeability with conventional 3D ...
BACKGROUND: The stroke volume (SV) can be measured by a human expert (HE) using the left ventricular outflow tract diameter (LVOTd) and its velocity t...
BACKGROUND: Degenerative cervical myelopathy (DCM) is the leading cause of spinal cord impairment worldwide, yet conventional magnetic resonance imagi...
BACKGROUND AND PURPOSE: Alzheimer's disease, a common type of dementia, gradually steals memories and impacts daily life as brain cells deteriorate. W...
Dementia is a growing global health challenge, and early identification is essential for timely intervention. We evaluated whether foundation model-ba...
OBJECTIVE: To evaluate the accuracy of a commercial deep learning algorithm in measuring spinopelvic parameters on full spine radiographs. MATERIALS A...
Epilepsy remains a major global health concern, particularly in regions where continuous medical monitoring is difficult to implement. This study intr...
BACKGROUND: Meningiomas, particularly large temporocorneal meningiomas, pose significant surgical challenges due to their proximity to critical brain ...
BACKGROUND: Asthma is a common chronic inflammatory airway disease. Accumulating evidence highlights the roles of demographic, lifestyle, and comorbid...
BACKGROUND: Artificial intelligence (AI) can improve stroke imaging workflows, but its computational carbon footprint remains poorly quantified. We es...
As critical metabolic biomarkers, amino acids exert essential physiological functions, and their abnormal levels are closely associated with a range o...