Latest AI and machine learning research in neurology for healthcare professionals.
PURPOSE: We sough to develop an automatic method of quantifying optic disc pallor in fundus photographs and determine associations with peripapillary retinal nerve fiber layer (pRNFL) thickness.
The deep learning-based automatic detection of epilepsy electroencephalogram (EEG), which can avoid the artificial influence, has attracted much attention, and its effectiveness mainly depends on the deep neural network model. In this paper, an attention-based multi-scale residual network (AMSRN) was proposed in consideration of the multiscale, spatio-temporal characteristics of epilepsy EEG and t...
Alzheimer's disease (AD) is a common and serious form of elderly dementia, but early detection and treatment of mild cognitive impairment can help slo...
This research introduces a novel dual-pathway convolutional neural network (DP-CNN) architecture tailored for robust performance in Log-Mel spectrogra...
BACKGROUND: Alzheimer's disease (AD) is an irreversible primary brain disease with insidious onset. The rise of imaging genetics research has led nume...
Machine learning (ML) approaches are increasingly being applied to neuroimaging data. Studies in neuroscience typically have to rely on a limited set ...
PURPOSE: Retinal and optic nerve diseases have become the primary cause of irreversible vision loss and blindness. However, there is still a lack of t...
A 52-year-old, Japanese man presented to the hospital with a complaint of anal bleeding, and detailed examination resulted in a diagnosis of locally a...
While neurological manifestations are core features of Fabry disease (FD), quantitative neuroimaging biomarkers allowing to measure brain involvement ...
OBJECTIVE: To evaluate the diagnostic performance and image quality of 1.5-mm slice thickness MRI with deep learning-based image reconstruction (1.5-m...
Novel features derived from imaging and artificial intelligence systems are commonly coupled to construct computer-aided diagnosis (CAD) systems that ...
OBJECTIVE: The evaluation of patients with headache relies heavily on the history. This article reviews key questions for diagnosing primary and secon...
INTRODUCTION: Stroke has emerged as the leading cause of disability globally. The provision of long-term rehabilitation to stroke survivors poses a he...
Spinocerebellar ataxia type 12 is a hereditary and neurodegenerative illness commonly found in India. However, there is no established noninvasive aut...
BACKGROUND: Adolescents with hemiplegic cerebral palsy undergo conventional physical therapy (CPT) to improve static and dynamic balance, activities o...
Glaucoma is a chronic neurodegenerative disease that can result in irreversible vision loss if not treated in its early stages. The cup-to-disc ratio ...
Given the prevalence of dementia and the development of pathology-specific disease-modifying therapies, high-value biomarker strategies to inform medi...
Deep convolutional neural networks (DCNNs) are able to partially predict brain activity during object categorization tasks, but factors contributing t...
To achieve meaningful, patient-centered outcomes following adult spinal deformity (ASD) surgery, it is crucial to engage in precise preoperative plann...
The objective of EEG-based emotion recognition is to classify emotions by decoding signals, with potential applications in the fields of artificial in...