Neurology

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

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Angular correlation-based feature selection for machine learning classification of manual automatisms using body sensor network data.

Automatisms are repetitive, semi-ordered movements often observed in focal impaired awareness seizur...

Topological Insulators Boost Ultralow-Power Neuromorphic Spintronics: Advancing Handwritten Digit Recognition with High SOT Efficiency.

Neuromorphic spintronics devices driven by spin-orbit torque (SOT) offer advantages in integration d...

Where are all the neurosurgery robots?

Despite substantial advances in engineering, robotics, and artificial intelligence, autonomous robot...

Optimal graph representations and neural networks for multichannel time series data in seizure phase classification.

In recent years, several machine-learning (ML) solutions have been proposed to solve the problems of...

An AI-assisted fluorescence microscopic system for screening mitophagy inducers by simultaneous analysis of mitophagic intermediates.

Mitophagy, the selective autophagic elimination of mitochondria, is essential for maintaining mitoch...

Decreased spinal inhibition leads to undiversified locomotor patterns.

During walking and running, animals display rich and coordinated motor patterns that are generated a...

Dynamically weighted graph neural network for detection of early mild cognitive impairment.

Alzheimer's disease (AD) is a prevalent neurodegenerative disease that primarily affects the elderly...

Assessing the impact of artifact correction and artifact rejection on the performance of SVM- and LDA-based decoding of EEG signals.

Numerous studies have demonstrated that eyeblinks and other large artifacts can decrease the signal-...

Causes and consequences of 'delays' in the diagnosis of spinal dural arterio-venous fistula; An illustrative case series, review and commentary.

BACKGROUND: Delays in management and misdiagnosis are common in patients with spinal dural arteriove...

Memristive neuromorphic interfaces: integrating sensory modalities with artificial neural networks.

The advent of the Internet of Things (IoT) has led to exponential growth in data generated from sens...

Evaluating the impact of human expertise in human-centered AI: A case study on finger-tapping video analysis for dementia detection.

PURPOSE: Human-centered artificial intelligence (AI) plays a crucial role in medical research. This ...

Machine learning-enhanced SERS diagnostics: Accelerating the AI-powered transition from laboratory discoveries to clinical practice.

Surface-enhanced Raman spectroscopy (SERS) has emerged as a transformative analytical tool in diseas...

Using machine learning to identify Parkinson's disease severity subtypes with multimodal data.

BACKGROUND: Classifying and predicting Parkinson's disease (PD) is challenging because of its divers...

Concept transfer of synaptic diversity from biological to artificial neural networks.

Recent developments in artificial neural networks have drawn inspiration from biological neural netw...

Role of astroglia and microglia in Alzheimer's disease and multiple therapeutic interventions.

Alzheimer's disease (AD) is characterized by deposition of amyloid-β (Aβ) and neurofibrillary tangle...

Interval type-2 intelligent fuzzy vehicle speed controller design using headlamp reflection detection and an adaptive neuro-fuzzy inference system.

In this study, we present an algorithm to estimate the distance between a vehicle and a target objec...

Neural Spectral Prediction for Structure Elucidation with Tandem Mass Spectrometry.

Structural elucidation using untargeted tandem mass spectrometry (MS/MS) has played a critical role ...

In vivo and in silico models of Drosophila for Parkinson's disease.

The fruit fly Drosophila melanogaster has emerged as an important model organism to shed light on ne...

DiaBD: A diabetes dataset for enhanced risk analysis and research in Bangladesh.

Diabetes is a chronic condition affecting millions worldwide and severely impacts health and quality...

Automated labeling using tracked ultrasound imaging: Application in tracking vertebrae during spine surgery.

PURPOSE: Recent advancements in machine learning (ML) allow for rapid analysis of complex image data...

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