Neurology

2D Materials Powering Neuromorphic Intelligence.

The exponential demand for energy-efficient and adaptive computing architectures drives the evolution of artificial intelligence (AI) and machine learning (ML). Neuromorphic computing, inspired by biological neural networks, overcomes the limitations of traditional von Neumann architectures, including high energy consumption and limited scalability. The introduction of two-dimensional (2D) materia...

Exploring Non-Embodied AI-Based Digital Companions for Older Adults in Aging and Care Contexts: Protocol for a Scoping Review.

BACKGROUND: Conversational artificial intelligence (AI) technologies are increasingly positioned as a response to social isolation, loneliness, and unmet psychosocial needs across health and care contexts. Non-embodied AI-based digital companions have attracted growing attention for their potential to support companionship, social interaction, communication, and psychosocial well-being among older...

Vision-Based Artificial Intelligence Technologies for Epilepsy Monitoring: Scoping Review and Taxonomy Development Study.

BACKGROUND: Artificial intelligence (AI) technologies for vision-based epilepsy monitoring are advancing rapidly in health care. Despite growing resea...

Enhancing Cognitive Functions of Older Adults With Software Robot: Longitudinal Exploratory Field Study.

BACKGROUND: The global prevalence of dementia continues to rise and demands scalable, nonpharmacological interventions. Digital cognitive training has...

Gait Analysis for Identifying Normal Cognition, Subjective Cognitive Decline, and Mild Cognitive Impairment in Parkinson Disease: Diagnostic Study.

BACKGROUND: Patients with Parkinson disease (PD) along with subjective cognitive decline (PD-SCD) are considered an intermediate status between those ...

Explainable and Interpretable AI for Voice and Speech Analysis in Clinical Care: Systematic Review.

BACKGROUND: Driven by recent advances in artificial intelligence (AI), particularly in medicine, audio-based voice and speech biomarkers are increasin...

Longitudinal Biomarker Trajectories for EVD-Associated Infection Prediction: A Trajectory-Based Machine Learning Framework with Biological Onset Characterization.

BACKGROUND: EVD-associated infection occurs in 1-40% of patients with indwelling external ventricular drains. Assessing cerebrospinal fluid (CSF) para...

Prediction of Early Hospital Admission (≤24 Hours) After Stroke Using Machine Learning and Deep Learning: Multicenter Study From China.

BACKGROUND: Timely hospital admission is a prerequisite for effective acute stroke management, yet a substantial proportion of patients fail to reach ...

Patient and Facility Factors Associated with Uptake of NTAP-Billed AI to Identify Suspected LVO in Ischemic Stroke.

PURPOSE: Medicare's New Technology Add-On Payment (NTAP) incentivizes the adoption of innovative technologies. We examined factors associated with the...

Spiking neural network decoders of finger forces from high-density intramuscular microelectrode arrays.

Assistive technologies for restoring naturalistic finger control require continuous and robust decoding of motor intent, with high accuracy and low la...

Discrete Wavelet Convolution for Learnable Time-Frequency Representation with Application to Seizure Prediction.

Accurate and adaptive time-frequency representation is essential for analyzing nonstationary signals in critical applications, such as epileptic seizu...

Metabolomic signatures of brain aging: A multimodal and genetic study.

Accelerated brain aging is increasingly recognized as a transdiagnostic risk factor for neuropsychiatric and neurodegenerative disorders, yet its meta...

6PPD-quinone exposure and Alzheimer's disease: insights from integrative network pharmacology, transcriptomics, machine learning, and molecular docking.

OBJECTIVES: To systematically investigate the molecular associations between 6PPD-quinone (6PPD-Q), an environmental transformation product of the tir...

FEDI-CODE: A federated and causally-informed framework for dementia risk prediction using multi-site patient data.

Early detection of dementia is critical for timely intervention and disease management, yet it remains a challenging task due to the fragmented nature...

Beyond the LUMIR challenge: The pathway to foundational registration models.

Medical image challenges have played a transformative role in advancing the field, catalyzing innovation and establishing new performance benchmarks. ...

Multi-strategy investigation identifies amentoflavone as a novel D3R antagonist for Parkinson's disease treatment.

BACKGROUND: Parkinson's disease (PD) still lacks therapies that can simultaneously improve symptoms and slow neurodegenerative progression, making the...

Retinal Vessel Traits and the Risk of Stroke: The Canadian Longitudinal Study on Aging.

PURPOSE: Retinal vascular changes could serve as an early, easily visible indicator of cerebrovascular health. Prior research on retinal vessel traits...

Vestibular cortex-related effective connectivity signatures: characterization and differentiation of vestibular migraine patients via magnetic resonance imaging and machine learning.

BACKGROUND: Neuroimaging studies of vestibular migraine (VM) have revealed abnormal functional connectivity in the central vestibular system. However,...

CT-based automatic segmentation of key CSF regions for detecting disproportionately enlarged subarachnoid space hydrocephalus.

BACKGROUND: Disproportionately enlarged subarachnoid space hydrocephalus (DESH) is a characteristic neuroimaging feature of idiopathic normal pressure...

Outer nuclear layer thinning as an in vivo biomarker for discriminating probable FTLD-tau from probable FTLD-TDP with PET-supported subtyping.

BACKGROUND AND OBJECTIVES: Outer nuclear layer (ONL) thinning has been identified in frontotemporal lobar degeneration (FTLD); however, its utility fo...