Neurology

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

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Damage explains function in spiking neural networks representing central pattern generator.

Complex biological systems have evolved to control movement dynamics despite noisy and unpredictable...

Identification of autism spectrum disorder using electroencephalography and machine learning: a review.

Autism Spectrum Disorder (ASD) is a neurodevelopmental condition characterized by communication barr...

Deep learning-based patient stratification for prognostic enrichment of clinical dementia trials.

Dementia probably due to Alzheimer's disease is a progressive condition that manifests in cognitive ...

Detecting fast-ripples on both micro- and macro-electrodes in epilepsy: A wavelet-based CNN detector.

BACKGROUND: Fast-ripples (FR) are short (∼10 ms) high-frequency oscillations (HFO) between 200 and 6...

ECG-based machine learning model for AF identification in patients with first ischemic stroke.

BACKGROUND: The recurrence rate of strokes associated with atrial fibrillation (AF) can be substanti...

DCA-Enhanced Alzheimer's detection with shearlet and deep learning integration.

Alzheimer's dementia (AD) is a neurodegenerative disorder that affects the central nervous system, c...

STCNet: Spatio-Temporal Cross Network with subject-aware contrastive learning for hand gesture recognition in surface EMG.

This paper introduces the Spatio-Temporal Cross Network (STCNet), a novel deep learning architecture...

How accurate are machine learning models in predicting anti-seizure medication responses: A systematic review.

IMPORTANCE: Current epilepsy management protocols often depend on anti-seizure medication (ASM) tria...

Design and Evaluation of Augmented Reality-Enhanced Robotic System for Epidural Interventions.

The epidural injection is a medical intervention to inject therapeutics directly into the vicinity o...

Advances in Machine Learning-Aided Thermal Imaging for Early Detection of Diabetic Foot Ulcers: A Review.

The prevention and early warning of foot ulcers are crucial in diabetic care; however, early microva...

Adapting to time: Why nature may have evolved a diverse set of neurons.

Brains have evolved diverse neurons with varying morphologies and dynamics that impact temporal info...

Neural networks with optimized single-neuron adaptation uncover biologically plausible regularization.

Neurons in the brain have rich and adaptive input-output properties. Features such as heterogeneous ...

Multimodal Alzheimer's disease classification through ensemble deep random vector functional link neural network.

Alzheimer's disease (AD) is a condition with a complex pathogenesis, sometimes hereditary, character...

Prediction of postoperative stroke in patients experienced coronary artery bypass grafting surgery: a machine learning approach.

BACKGROUND: Coronary artery bypass grafting (CABG) surgery has been a widely accepted method for tre...

A machine learning approach for identifying anatomical biomarkers of early mild cognitive impairment.

BACKGROUND: Alzheimer's Disease (AD) poses a major challenge as a neurodegenerative disorder, and ea...

Random survival forest model for early prediction of Alzheimer's disease conversion in early and late Mild cognitive impairment stages.

With a clinical trial failure rate of 99.6% for Alzheimer's Disease (AD), early diagnosis is critica...

Neurocontrol for fixed-length trajectories in environments with soft barriers.

In this paper we present three neurocontrol problems where the analytic policy gradient via back-pro...

Artificial intelligence in emergency neuroradiology: Current applications and perspectives.

Emergency neuroradiology provides rapid diagnostic decision-making and guidance for management for a...

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