Neurology

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

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Statistical and Machine Learning Analysis in Brain-Imaging Genetics: A Review of Methods.

Brain-imaging-genetic analysis is an emerging field of research that aims at aggregating data from n...

Fluorescent Neuronal Cells v2: multi-task, multi-format annotations for deep learning in microscopy.

Fluorescent Neuronal Cells v2 is a collection of fluorescence microscopy images and the correspondin...

Spine surgeon versus AI algorithm full-length radiographic measurements: a validation study of complex adult spinal deformity patients.

INTRODUCTION: Spinal measurements play an integral role in surgical planning for a variety of spine ...

Using brain structural neuroimaging measures to predict psychosis onset for individuals at clinical high-risk.

Machine learning approaches using structural magnetic resonance imaging (sMRI) can be informative fo...

Prediction of dementia based on older adults' sleep disturbances using machine learning.

BACKGROUND: The most common degenerative condition in older adults is dementia, which can be predict...

Automated detection of fatal cerebral haemorrhage in postmortem CT data.

During the last years, the detection of different causes of death based on postmortem imaging findin...

Artificial intelligence for drug discovery and development in Alzheimer's disease.

The complex molecular mechanism and pathophysiology of Alzheimer's disease (AD) limits the developme...

Neuromonitoring in the ICU - what, how and why?

PURPOSE OF REVIEW: We selectively review emerging noninvasive neuromonitoring techniques and the evi...

Applied deep learning in neurosurgery: identifying cerebrospinal fluid (CSF) shunt systems in hydrocephalus patients.

BACKGROUND: Over the recent decades, the number of different manufacturers and models of cerebrospin...

Autosomal recessive cerebellar ataxias: a diagnostic classification approach according to ocular features.

Autosomal recessive cerebellar ataxias (ARCAs) are a heterogeneous group of neurodegenerative disord...

Oral_voting_transfer: classification of oral microorganisms' function proteins with voting transfer model.

INTRODUCTION: The oral microbial group typically represents the human body's highly complex microbia...

Identification of key genes as potential diagnostic and therapeutic targets for comorbidity of myasthenia gravis and COVID-19.

INTRODUCTION: Myasthenia gravis (MG) is a chronic autoimmune neuromuscular disorder. Coronavirus dis...

Classification of EMG signals with CNN features and voting ensemble classifier.

Electromyography (EMG) signals are primarily used to control prosthetic hands. Classifying hand gest...

Self-Supervised Learning for Electroencephalography.

Decades of research have shown machine learning superiority in discovering highly nonlinear patterns...

Snippet Policy Network V2: Knee-Guided Neuroevolution for Multi-Lead ECG Early Classification.

Early time series classification predicts the class label of a given time series before it is comple...

Towards a diagnostic tool for neurological gait disorders in childhood combining 3D gait kinematics and deep learning.

Gait abnormalities are frequent in children and can be caused by different pathologies, such as cere...

Potential merits and flaws of large language models in epilepsy care: A critical review.

The current pace of development and applications of large language models (LLMs) is unprecedented an...

Naturally occurring caffeic acid phenethyl ester from chestnut honey-based propolis and virtual screening towards DYRK1A.

Neurodegenerative diseases (NDDs) are disorders with dysfunction and ongoing loss of neurons, glial ...

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