Latest AI and machine learning research in neurology for healthcare professionals.
Numerous brain disorders are associated with ventriculomegaly, including both neuro-degenerative diseases and cerebrospinal fluid disorders. Detailed evaluation of the ventricular system is important for these conditions to help understand the pathogenesis of ventricular enlargement and elucidate novel patterns of ventriculomegaly that can be associated with different diseases. One such disease is...
Human activity recognition has become an active research field over the past few years due to its wide application in various fields such as health-care, smart home monitoring, and surveillance. Existing approaches for activity recognition in smart homes have achieved promising results. Most of these approaches evaluate real-time recognition of activities using only sensor activations that precede...
OBJECTIVE: Sudden unexpected death in epilepsy (SUDEP) is an important cause of mortality in epilepsy. However, there is a gap in how often providers ...
Detecting cerebral microbleeds (CMBs) is important in diagnosing a variety of diseases including dementia, stroke and traumatic brain injury. However,...
OBJECTIVE: The objective of this study was to build a supervised machine learning-based classifier, which can accurately predict the outcomes of antie...
INTRODUCTION: Primary progressive aphasia (PPA) is a clinical syndrome of neurodegenerative origin with 3 main variants: non-fluent, semantic, and log...
BACKGROUND AND OBJECTIVES: Clathrin is an adaptor protein that serves as the principal element of the vesicle-coating complex and is important for the...
Computer-aided diagnosis has become a widely-used auxiliary tool for the diagnosis of Alzheimer's disease (AD). In this study, we developed an extreme...
BACKGROUND: Neuroimaging analysis is currently crucial for an early assessment of glioblastoma, to help improving treatment and tumor follow-up. To th...
Background and Purpose- Automatic segmentation of cerebral infarction on diffusion-weighted imaging (DWI) is typically performed based on a fixed appa...
This paper introduces a novel electroencephalogram (EEG) data classification scheme together with its implementation in hardware using an innovative a...
Neuropathologists assess vast brain areas to identify diverse and subtly-differentiated morphologies. Standard semi-quantitative scoring approaches, h...
The laminar organization of the cerebral cortex is a fundamental characteristic of the brain, with essential implications for cortical function. Due t...
OBJECTIVE: Evaluation of a data-driven, model-based classification approach to discriminate idiopathic Parkinson's disease (PD) patients from healthy ...
Emotion recognition based on multi-channel electroencephalograph (EEG) signals is becoming increasingly attractive. However, the conventional methods ...
Severe spinal cord injury (SCI) leads to skeletal muscle atrophy and adipose tissue infiltration in the skeletal muscle, which can result in compromis...
Motor imagery electroencephalography (EEG) decoding is an essential part of brain-computer interfaces (BCIs) which help motor-disabled patients to com...
Social isolation is one of the most common consequences of older people with dementia, especially for those who live at their own dwellings alone due ...
Stroke is the main cause of disability after age 65, leaving survivors with sequels that require care and recovery treatment lasting years. It is esti...
Subtle changes in hippocampal volumes may occur during both physiological and pathophysiological processes in the human brain. Assessing hippocampal v...