Neurology

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

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Diagnostic biomarker discovery from brain EEG data using LSTM, reservoir-SNN, and NeuCube methods in a pilot study comparing epilepsy and migraine.

The study introduces a new online spike encoding algorithm for spiking neural networks (SNN) and sug...

Machine learning decoding of single neurons in the thalamus for speech brain-machine interfaces.

. Our goal is to decode firing patterns of single neurons in the left ventralis intermediate nucleus...

Artificial Intelligence in the Future Landscape of Pediatric Neuroradiology: Opportunities and Challenges.

This paper will review how artificial intelligence (AI) will play an increasingly important role in ...

Natural language processing augments comorbidity documentation in neurosurgical inpatient admissions.

OBJECTIVE: To establish whether or not a natural language processing technique could identify two co...

Association Between Sleep Quality and Deep Learning-Based Sleep Onset Latency Distribution Using an Electroencephalogram.

To evaluate sleep quality, it is necessary to monitor overnight sleep duration. However, sleep monit...

A Siamese Convolutional Neural Network for Identifying Mild Traumatic Brain Injury and Predicting Recovery.

Timely diagnosis of mild traumatic brain injury (mTBI) remains challenging due to the rapid recovery...

Robot-based solution for helping Alzheimer patients.

Alzheimer's is a progressive and debilitating neurological disorder characterized by cognitive decli...

Artificial intelligence in epilepsy - applications and pathways to the clinic.

Artificial intelligence (AI) is rapidly transforming health care, and its applications in epilepsy h...

Ξ—and dexterities assessment in stroke patients based on augmented reality and machine learning through a box and block test.

A popular and widely suggested measure for assessing unilateral hand motor skills in stroke patients...

Pain prediction model based on machine learning and SHAP values for elders with dementia in Taiwan.

INTRODUCTION: Pain conditions are common in elderly individuals, including those with dementia. Howe...

Deciphering seizure semiology in corpus callosum injuries: A comprehensive systematic review with machine learning insights.

INTRODUCTION: Seizure disorders have often been found to be associated with corpus callosum injuries...

Ethical Incorporation of Artificial Intelligence into Neurosurgery: A Generative Pretrained Transformer Chatbot-Based, Human-Modified Approach.

INTRODUCTION: Artificial intelligence (AI) has become increasingly used in neurosurgery. Generative ...

EEG classification model for virtual reality motion sickness based on multi-scale CNN feature correlation.

BACKGROUND: Virtual reality motion sickness (VRMS) is a key issue hindering the development of virtu...

Utilizing machine learning to facilitate the early diagnosis of posterior circulation stroke.

BACKGROUND: Posterior Circulation Syndrome (PCS) presents a diagnostic challenge characterized by it...

Prediction and causal inference of cardiovascular and cerebrovascular diseases based on lifestyle questionnaires.

Cardiovascular and cerebrovascular diseases (CCVD) are prominent mortality causes in Japan, necessit...

Combining enhanced spectral resolution of EMG and a deep learning approach for knee pathology diagnosis.

Knee osteoarthritis (OA) is a prevalent, debilitating joint condition primarily affecting the elderl...

Dimensional Neuroimaging Endophenotypes: Neurobiological Representations of Disease Heterogeneity Through Machine Learning.

Machine learning has been increasingly used to obtain individualized neuroimaging signatures for dis...

Machine learning-empowered sleep staging classification using multi-modality signals.

The goal is to enhance an automated sleep staging system's performance by leveraging the diverse sig...

A new era in cognitive neuroscience: the tidal wave of artificial intelligence (AI).

Translating artificial intelligence techniques into the realm of cognitive neuroscience holds promis...

Detecting emotions through EEG signals based on modified convolutional fuzzy neural network.

Emotion is a human sense that can influence an individual's life quality in both positive and negati...

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