Neurology

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

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Neurofind: using deep learning to make individualised inferences in brain-based disorders.

Within precision psychiatry, there is a growing interest in normative models given their ability to ...

Prediction and validation of anoikis-related genes in neuropathic pain using machine learning.

BACKGROUND: Neuropathic pain (NP) can be induced by a variety of clinical conditions, such as spinal...

Evaluation of AI-based nerve segmentation on ultrasound: relevance of standard metrics in the clinical setting.

BACKGROUND: In artificial intelligence for ultrasound-guided regional anaesthesia, accurate nerve id...

CSEPC: a deep learning framework for classifying small-sample multimodal medical image data in Alzheimer's disease.

BACKGROUND: Alzheimer's disease (AD) is a neurodegenerative disorder that significantly impacts heal...

Development and validation of a machine learning approach for screening new leprosy cases based on the leprosy suspicion questionnaire.

Leprosy is a dermatoneurological disease and can cause irreversible nerve damage. In addition to bei...

Estimation of Machine Learning-Based Models to Predict Dementia Risk in Patients With Atherosclerotic Cardiovascular Diseases: UK Biobank Study.

BACKGROUND: The atherosclerotic cardiovascular disease (ASCVD) is associated with dementia. However,...

Artificial Intelligence and Predictive Modeling in the Management and Treatment of Episodic Migraine.

PURPOSE OF REVIEW: Artificial intelligence (AI) has impacted different aspects of headache medicine,...

CycleH-CUT: an unsupervised medical image translation method based on cycle consistency and hybrid contrastive learning.

Unsupervised medical image translation tasks are challenging due to the difficulty of obtaining perf...

Interpretable modality-specific and interactive graph convolutional network on brain functional and structural connectomes.

Both brain functional connectivity (FC) and structural connectivity (SC) provide distinct neural mec...

Applications of Artificial Intelligence in Neurosurgery for Improving Outcomes Through Diagnostics, Predictive Tools, and Resident Education.

BACKGROUND: Artificial intelligence (AI) has become an increasingly prominent tool in the field of n...

Linguistic cues for automatic assessment of Alzheimer's disease across languages.

BackgroundMost common forms of dementia, including Alzheimer's disease, are associated with alterati...

Of Pilots and Copilots: The Evolving Role of Artificial Intelligence in Clinical Neurophysiology.

Artificial intelligence (AI) is revolutionizing clinical neurophysiology (CNP), particularly in its ...

Hybrid CNN-GRU Models for Improved EEG Motor Imagery Classification.

Brain-computer interfaces (BCIs) based on electroencephalography (EEG) enable neural activity interp...

Urban and rural disparities in stroke prediction using machine learning among Chinese older adults.

Stroke is a significant health concern in China. Differences in stroke risk between rural and urban ...

A feature explainability-based deep learning technique for diabetic foot ulcer identification.

Diabetic foot ulcers (DFUs) are a common and serious complication of diabetes, presenting as open so...

Comprehensive clinical scale-based machine learning model for predicting subthalamic nucleus deep brain stimulation outcomes in Parkinson's disease.

Parkinson's Disease (PD) is a growing burden with varied clinical manifestations and responses to Su...

Deep learning to quantify the pace of brain aging in relation to neurocognitive changes.

Brain age (BA), distinct from chronological age (CA), can be estimated from MRIs to evaluate neuroan...

Inductive reasoning with large language models: A simulated randomized controlled trial for epilepsy.

INTRODUCTION: To investigate the potential of using artificial intelligence (AI), specifically large...

Cognitive performance classification of older patients using machine learning and electronic medical records.

Dementia rates are projected to increase significantly by 2050, posing considerable challenges for h...

Electroencephalogram (EEG) Based Fuzzy Logic and Spiking Neural Networks (FLSNN) for Advanced Multiple Neurological Disorder Diagnosis.

Neurological disorders are a major global health concern that have a substantial impact on death rat...

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