Neurology

Latest AI and machine learning research in neurology for healthcare professionals.

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Characteristics and Validity of Commercially Available Technologies Analyzing Voice Features to Assess Parkinson's Disease.

BACKGROUND: Interest in technologies for quantitative assessment of Parkinson's disease (PD) is grow...

Short-horizon neonatal seizure prediction using EEG-based deep learning.

Strategies to predict neonatal seizure risk have typically focused on long-term static predictions w...

Biomarkers and therapeutic strategies targeting microglia in neurodegenerative diseases: current status and future directions.

Recent advances in our understanding of non-cell-autonomous mechanisms in neurodegenerative diseases...

Sustainable analysis of COVID-19 Co-packaged paxlovid: exploring advanced sampling techniques and multivariate processing tools.

The drawbacks of random sampling not only hinder the development of more reliable and efficient meth...

Bridging molecular and cellular neuroscience with proximity labeling technologies.

Proximity labeling (PL) techniques have advanced neuroscience by revealing the molecular interaction...

How EEG preprocessing shapes decoding performance.

Electroencephalography (EEG) preprocessing varies widely between studies, but its impact on classifi...

Machine learning models predict risk of lower extremity deep vein thrombosis in hospitalized patients with spontaneous intracerebral hemorrhage.

Lower extremity deep vein thrombosis is one of the important complications of spontaneous intracereb...

Automated tick classification using deep learning and its associated challenges in citizen science.

Lyme borreliosis and tick-borne encephalitis significantly impact public health in Europe, transmitt...

An Efficient FoG-M3 Method for Self-Adaptive Labeling and Predicting Freezing of Gait.

Freezing of gait (FoG) is a common motor impairment that occurs as Parkinson's disease patients ente...

Prediction of Cerebrospinal Fluid (CSF) Pressure with Generative Adversarial Network Synthetic Plasma-CSF Biomarker Pairing.

Non-invasive intracranial pressure (ICP) monitoring can help clinicians safely and efficiently monit...

A transformer-based network with second-order pooling for motor imagery EEG classification.

. Electroencephalography (EEG) signals can reflect motor intention signals in the brain. In recent y...

An investigation of multimodal EMG-EEG fusion strategies for upper-limb gesture classification.

. Upper-limb gesture identification is an important problem in the advancement of robotic prostheses...

Improving meningitis surveillance and diagnosis with machine learning: Insights from São Paulo.

INTRODUCTION: Meningitis, an inflammatory condition of the membranes surrounding the brain and spina...

BN-SNN: Spiking neural networks with bistable neurons for object detection.

Spiking neural networks (SNNs) are emerging as a promising evolution in neural network paradigms, of...

A machine learning model reveals invisible microscopic variation in acute ischaemic stroke (≤ 6 h) with non-contrast computed tomography.

BACKGROUND: In most medical centers, particularly in primary hospitals, non-contrast computed tomogr...

Enhancing automated detection and classification of dementia in individuals with cognitive impairment using artificial intelligence techniques.

Dementia is a degenerative and chronic disorder, increasingly prevalent among older adults, posing s...

Machine learning for synchronous bone metastasis risk prediction in high grade lung neuroendocrine carcinoma.

Bone metastasis (BM) is common in high-grade lung neuroendocrine tumors (NETs). This study aimed to ...

Deep ensemble learning with transformer models for enhanced Alzheimer's disease detection.

The progression of Alzheimer's disease is relentless, leading to a worsening of mental faculties ove...

A Composable Channel-Adaptive Architecture for Seizure Classification.

Multi-variate time-series are one of the primary data modalities involved in large classes of proble...

Detection of focal impaired awareness seizures using a biometric shirt.

OBJECTIVE: In recent years, seizure detection using wearable technology has gained significant atten...

Inferring concussion history in athletes using pose and ground reaction force estimation and stability analysis of plyometric exercise videos.

Concussions present a significant risk to athletes, with females exhibiting higher rates and prolong...

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