Neurology

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

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A machine learning artefact detection method for single-channel infant event-related potential studies.

. Automated detection of artefact in stimulus-evoked electroencephalographic (EEG) data recorded in ...

Explainable machine learning on baseline MRI predicts multiple sclerosis trajectory descriptors.

Multiple sclerosis (MS) is a multifaceted neurological condition characterized by challenges in time...

Apple Intelligence in neurosurgery.

With the current artificial intelligence (AI) boom, new innovative and accessible applications requi...

HT_PREDICT: a machine learning-based computational open-source tool for screening HDAC6 inhibitors.

Histone deacetylase 6 (HDAC6) is a promising drug target for the treatment of human diseases such as...

Neuropsychological and electrophysiological measurements for diagnosis and prediction of dementia: a review on Machine Learning approach.

INTRODUCTION: Emerging and advanced technologies in the field of Artificial Intelligence (AI) repres...

Identification and diagnosis of schizophrenia based on multichannel EEG and CNN deep learning model.

This paper proposes a high-accuracy EEG-based schizophrenia (SZ) detection approach. Unlike comparab...

Disentangling brain atrophy heterogeneity in Alzheimer's disease: A deep self-supervised approach with interpretable latent space.

Alzheimer's disease (AD) is heterogeneous, but existing methods for capturing this heterogeneity thr...

Seizure Detection of EEG Signals Based on Multi-Channel Long- and Short-Term Memory-Like Spiking Neural Model.

Seizure is a common neurological disorder that usually manifests itself in recurring seizure, and th...

Automatic 3D reconstruction of vertebrae from orthogonal bi-planar radiographs.

When conducting spine-related diagnosis and surgery, the three-dimensional (3D) upright posture of t...

A robot-based hybrid lower limb system for Assist-As-Needed rehabilitation of stroke patients: Technical evaluation and clinical feasibility.

BACKGROUND: Although early rehabilitation is important following a stroke, severely affected patient...

Smart Cushions with Machine Learning-Enhanced Force Sensors for Pressure Injury Risk Assessment.

Prolonged sitting can easily result in pressure injury (PI) for certain people who have had strokes ...

Optimized efficient attention-based network for facial expressions analysis in neurological health care.

Facial Expression Analysis (FEA) plays a vital role in diagnosing and treating early-stage neurologi...

Morphological classification of neurons based on Sugeno fuzzy integration and multi-classifier fusion.

In order to extract more important morphological features of neuron images and achieve accurate clas...

Multi-Modal Electrophysiological Source Imaging With Attention Neural Networks Based on Deep Fusion of EEG and MEG.

The process of reconstructing underlying cortical and subcortical electrical activities from Electro...

Improving brain atrophy quantification with deep learning from automated labels using tissue similarity priors.

Brain atrophy measurements derived from magnetic resonance imaging (MRI) are a promising marker for ...

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