Latest AI and machine learning research in neurology for healthcare professionals.
OBJECTIVE: This study aimed to retrospectively analyze consultations requested from the emergency departments (EDs) to the neurosurgery (NS) department of a tertiary care hospital, and to comprehensively evaluate the clinical characteristics, referral reasons, and diagnostic and therapeutic processes of these patients. In addition, the study aims to provide concrete recommendations for strategic o...
Ferroptosis, an iron-dependent regulated cell death form, is a key pathogenic mechanism in Alzheimer's disease (AD), especially in the entorhinal cortex, a brain region selectively vulnerable to early AD neuropathology. This study aimed to identify peroxiredoxin 6 (PRDX6) as a novel ferroptosis-related hub gene in the entorhinal cortex and validate its diagnostic and therapeutic potential in AD. G...
BACKGROUND AND OBJECTIVE: Worldwide, over 50 million people suffer from epilepsy, a neurological disorder characterised by recurrent seizures due to a...
BACKGROUND: Heterogeneity in the long-term progression of Alzheimer's disease (AD) challenges the efficiency of clinical trials. Identifying long-term...
Aging is associated with widespread structural and functional changes in the brain including reduced neural plasticity, slower information processing,...
BACKGROUND: Cognitive dysfunction is common in people with epilepsy (PWE). Although expectations exist for deficits based on diagnosis, phenotypic var...
Neurodegenerative diseases represent a major and growing clinical challenge due to their progressive nature, biological heterogeneity, and limited the...
Stroke is one of the leading causes of mortality and long-term disability worldwide, primarily resulting from the sudden disruption of cerebral blood ...
Photon-counting detector CT myelography is an effective technique for the localization of spinal CSF leaks. The initial studies describing this techni...
Objective. Epilepsy is a chronic brain disorder characterized by recurrent seizures due to abnormal neuronal firing. Electroencephalogram (EEG)-based ...
STUDY DESIGN: Retrospective two-center external validation study conducted at two medical centers, collecting cervical spine MRI data from patients su...
BACKGROUND: Magnetic resonance imaging (MRI) in children requires multiple sequences, leading to lengthy exams and motion-related challenges. Syntheti...
OBJECTIVE: This paper presents a two-stage machine learning model for electrographic seizure detection using wearable single-channel scalp electroence...
Epilepsy is the fourth most common neurological disorder, and seizures significantly impact quality of life of affected individuals. Electroencephalog...
OBJECTIVE: Rapid and accurate mapping of brain tissue pH is crucial for early diagnosis and management of ischemic stroke. Amide proton transfer (APT)...
Auditory-evoked EEG signals contain rich temporal and cognitive features that reflect both the identity of individuals and their neural response to ex...
In neuroscience, joint receptors have traditionally been viewed as limit detectors, providing positional information only at extreme joint angles, whi...
Adolescent spinal postural deviations are rising across Southeast Asia, driven by prolonged screen exposure and limited access to clinical screening i...
The ability of machines to recognize emotions automatically is becoming increasingly significant across many domains where emotional understanding is ...
Stroke-associated pneumonia (SAP) is a frequent and severe complication following stroke. Recently, several machine learning (ML) models have been dev...