Neurology

An Automated Framework and Medical Intelligent System for MRI-Based Alzheimer's Diagnosis Classification.

In the era of artificial intelligence (AI), Alzheimer's disease (AD) can be diagnosed through magnetic resonance imaging (MRI) at accurate times and with precision to make effective clinical interventions. Nevertheless, classification is still problematic because of low-contrast anatomical structures, inter-class variations, imbalances of the classes, and the possibility of data leakage in slice-b...

Multilayered microelectrode array for monitoring electrophysiological signals of 3d neural networks in cerebral organoid.

Microelectrode arrays (MEAs) are widely used platforms for monitoring neuronal activity in biological systems. The advent of brain organoid technology-three-dimensional (3D) neural tissue models derived from human stem cells-has opened unprecedented opportunities to study network connectivity and developmental processes of brain-like tissues in vitro. However, most commercial MEAs are restricted t...

Dementia Prediction Using Gait Analysis and Machine Learning.

Dementia is a progressive neurodegenerative disorder affecting millions of people worldwide. Early prediction of dementia, especially during the mild ...

Prediction of Early Functional Outcome After Acute Ischemic Stroke Using Real-World Clinical Data in Vietnam and Indonesia: Retrospective Cohort Study.

Accurate prediction of early functional outcome after acute ischemic stroke is critical for clinical decision-making. This retrospective cohort study ...

Headache Diagnosis with Open Language Models on German Vignettes: Study Protocol.

Headache disorders present diagnostic challenges due to their clinical heterogeneity and the extensive taxonomy of the ICHD-3 classification. While la...

Machine Learning Applications Within the Earlier Medicine Framework for Stroke: A Scoping Review.

This scoping review explores how machine learning (ML) has been applied to stroke research within the Earlier Medicine framework, which promotes proac...

OPTIMA-DAW: Improving Cerebral Vasospasm Detection After Aneurysmal Subarachnoid Haemorrhage Using Machine Learning.

Cerebral vasospasm is a serious complication after aneurysmal subarachnoid haemorrhage (aSAH). We trained machine learning models on 168 patients (225...

AI-Integrated EEG Decision Support for Neurocritical Care: A Conceptual and Feasibility Framework.

The clinical use of electroencephalography (EEG) for neuro-prognostication in neurocritical care remains limited, despite its ability to provide non-i...

Explainable Machine Learning for Parkinson's Disease Screening Using Spiral Drawing Test.

Parkinson's disease (PD) is a common neurological disorder that can severely affect the patient's quality of life. The Archimedean spiral drawing test...

Exploring the Personalisation of Digital Cognitive Rehabilitation in Multiple Sclerosis Through Wearable Data and Machine Learning.

Cognitive impairment is a frequent, disabling symptom of multiple sclerosis (MS). Digital interventions may help people with MS maintain or improve co...

Evaluating the Role of Order and Time Information for Classifying Sequences of Healthcare Events Derived from Claims Data.

Sequences of healthcare events from claims data are increasingly used for predictive modeling. Despite the rise in popularity of neural networks, the ...

Identification of Reliable Biomarkers for ALS Through Machine Learning Approach.

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disorder characterized by progressive motor neuron degeneration and limited diagnosti...

Integrative multi-omics analysis reveals host-microbiome metabolic alterations and candidate biomarkers in Parkinson's disease.

Alterations in the gut microbiome have been increasingly implicated in Parkinson's disease (PD), but the associated metabolic changes remain incomplet...

Predicting future dementia from routine clinical MRI and linked healthcare data.

BACKGROUND: Early identification of individuals at risk of dementia is essential for preventive care and timely enrolment into disease-modifying inter...

Spatio-Temporal Attention with Spiking Neural Networks for Seizure Detection from Electroencephalogram Signals.

Timely and accurate detection of seizures from Electroencephalogram (EEG) signals is critical for the effective management of epilepsy. Although deep ...

"Bioprinting of Hair: How Far We Proceeded and What Needs to be Done".

Alopecia is a common dermatologic disorder with psychological and quality-of-life impact. Current options such as PRP, topical agents, microneedling o...

Artificial intelligence for detection and staging of Alzheimer's disease using retinal images.

This is a protocol for a Cochrane Review (diagnostic). The objectives are as follows: To determine the diagnostic accuracy of AI algorithm-based retin...

Proximal Junctional Kyphosis Prevention in Adult Spinal Deformity Surgery: A Technical Review of Tethering and Adjunctive Strategies.

BACKGROUND AND OBJECTIVES: Proximal junctional kyphosis (PJK) and proximal junctional failure (PJF) remain significant complications after long-segmen...

Decoding shared pathogenic networks of oxidative stress in neuropsychiatric disorders to prioritize multi-target therapeutics from natural products.

BACKGROUND: Neurodegenerative and psychiatric disorders, including Alzheimer's disease (AD), Parkinson's disease (PD), Huntington's disease (HD), and ...

Upregulation of the Mitophagy-Related Gene EXOSC4 Is Associated with Immune Dysregulation in Spinal Cord Injury.

Spinal cord injury (SCI) profoundly impairs patients' quality of life and imposes a substantial economic burden on society, often resulting in irrever...