Neurology

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

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Specialized Large Language Model Outperforms Neurologists at Complex Diagnosis in Blinded Case-Based Evaluation.

: Artificial intelligence (AI), particularly large language models (LLMs), has demonstrated versatil...

An Assessment of the Performance of Different Chatbots on Shoulder and Elbow Questions.

The utility of artificial intelligence (AI) in medical education has recently garnered significant ...

Recurrent and convolutional neural networks in classification of EEG signal for guided imagery and mental workload detection.

The Guided Imagery technique is reported to be used by therapists all over the world in order to inc...

Predicting quality of life of patients after treatment for spinal metastatic disease: development and internal evaluation.

BACKGROUND CONTEXT: When treating spinal metastases in a palliative setting, maintaining or enhancin...

Physiological Sensor Modality Sensitivity Test for Pain Intensity Classification in Quantitative Sensory Testing.

Chronic pain is prevalent and disproportionately impacts adults with a lower quality of life. Althou...

The effect of lower limb rehabilitation robot on lower limb -motor function in stroke patients: a systematic review and meta-analysis.

BACKGROUND: The assessment and enhancement of lower limb motor function in hemiplegic patients is of...

A Machine Learning Approach to Predict Cognitive Decline in Alzheimer Disease Clinical Trials.

BACKGROUND AND OBJECTIVES: Among the participants of Alzheimer disease (AD) treatment trials, 40% do...

Ensemble network using oblique coronal MRI for Alzheimer's disease diagnosis.

Alzheimer's disease (AD) is a primary degenerative brain disorder commonly found in the elderly, Mil...

Accuracy and quality of ChatGPT-4o and Google Gemini performance on image-based neurosurgery board questions.

Large-language models (LLMs) have shown the capability to effectively answer medical board examinati...

Select for better learning: identifying high-quality training data for a multimodal cyclic transformer.

. Tonic-clonic seizures (TCSs), which present a significant risk for sudden unexpected death in epil...

Neurorehabilitation in spinal cord injury: Increased cortical activity through tDCS and robotic gait training.

OBJECTIVE: This study investigates the neurophysiological outcomes of combining robot-assisted gait ...

Eye movement detection using electrooculography and machine learning in cardiac arrest patients.

AIM: To train a machine learning algorithm to identify eye movement from electrooculography (EOG) in...

Using machine learning to simultaneously quantify multiple cognitive components of episodic memory.

Why do we remember some events but forget others? Previous studies attempting to decode successful v...

Bio-inspired neural networks with central pattern generators for learning multi-skill locomotion.

Biological neural circuits, central pattern generators (CPGs), located at the spinal cord are the un...

Integrating data mining with transcranial focused ultrasound to refine neuralgia treatment strategies.

BACKGROUND: Neuralgia and other neuropathic pain are difficult to treat owing to their complicated e...

New approach to specific Alzheimer's disease diagnosis based on plasma biomarkers in a cognitive disorder cohort.

BACKGROUND: The validation of a combination of plasma biomarkers and demographic variables is requir...

SpineMamba: Enhancing 3D spinal segmentation in clinical imaging through residual visual Mamba layers and shape priors.

Accurate segmentation of three-dimensional (3D) clinical medical images is critical for the diagnosi...

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