AI Medical Compendium Journal:
BMC neurology

Showing 21 to 30 of 40 articles

Robot-assisted percutaneous balloon compression for trigeminal neuralgia- preliminary experiences.

BMC neurology
OBJECTIVES: This study aims to discuss the availability of robot-assisted percutaneous balloon compression (PBC) for trigeminal neuralgia (TN) and share our preliminary experiences.

Developing DELPHI expert consensus rules for a digital twin model of acute stroke care in the neuro critical care unit.

BMC neurology
INTRODUCTION: Digital twins, a form of artificial intelligence, are virtual representations of the physical world. In the past 20 years, digital twins have been utilized to track wind turbines' operations, monitor spacecraft's status, and even create...

Predictive nomogram for soft robotic hand rehabilitation of patients with intracerebral hemorrhage.

BMC neurology
BACKGROUND: Few studies focused on the risk factors for hand rehabilitation of intracerebral hemorrhage (ICH) using of soft robotic hand therapy (SRHT). The aim of this study was to establish a predictive nomogram for soft robotic hand rehabilitation...

Effectiveness of robot-assisted virtual reality mirror therapy for upper limb motor dysfunction after stroke: study protocol for a single-center randomized controlled clinical trial.

BMC neurology
BACKGROUND: Upper limb motor dysfunction is a common sequela of stroke, and its clinical efficacy needs to be improved. This protocol describes a trial to verify the clinical efficacy of robot-assisted virtual reality mirror therapy (RAVRMT) in impro...

Risk prediction of 30-day mortality after stroke using machine learning: a nationwide registry-based cohort study.

BMC neurology
BACKGROUNDS: We aimed to develop and validate machine learning (ML) models for 30-day stroke mortality for mortality risk stratification and as benchmarking models for quality improvement in stroke care.

Deep learning algorithm to evaluate cervical spondylotic myelopathy using lateral cervical spine radiograph.

BMC neurology
BACKGROUND: Deep learning (DL) is an advanced machine learning approach used in different areas such as image analysis, bioinformatics, and natural language processing. A convolutional neural network (CNN) is a representative DL model that is highly ...

Agreement between neuroimages and reports for natural language processing-based detection of silent brain infarcts and white matter disease.

BMC neurology
BACKGROUND: There are numerous barriers to identifying patients with silent brain infarcts (SBIs) and white matter disease (WMD) in routine clinical care. A natural language processing (NLP) algorithm may identify patients from neuroimaging reports, ...

A deep learning model for diagnosing dystrophinopathies on thigh muscle MRI images.

BMC neurology
BACKGROUND: Dystrophinopathies are the most common type of inherited muscular diseases. Muscle biopsy and genetic tests are effective to diagnose the disease but cost much more than primary hospitals can reach. The more available muscle MRI is promis...

A self-administered, artificial intelligence (AI) platform for cognitive assessment in multiple sclerosis (MS).

BMC neurology
BACKGROUND: Cognitive impairment is common in patients with multiple sclerosis (MS). Accurate and repeatable measures of cognition have the potential to be used as markers of disease activity.

Rehabilitation of older people with Parkinson's disease: an innovative protocol for RCT study to evaluate the potential of robotic-based technologies.

BMC neurology
BACKGROUND: Parkinson's disease is one of the most frequent causes of disability among the older adults. It is a chronic-progressive neuro-degenerative disease, characterized by several motor disorders. Balance disorders are a symptom that involves t...