Neurology

Artificial intelligence for adult spinal deformity: current state and future directions.

As we experience a technological revolution unlike any other time in history, spinal surgery as a discipline is poised to undergo a dramatic transformation. As enormous amounts of data become digitized and more readily available, medical professionals approach a critical juncture with respect to how advanced computational techniques may be incorporated into clinical practices. Within neurosurgery,...

Simultaneous imputation and classification using Multigraph Geometric Matrix Completion (MGMC): Application to neurodegenerative disease classification.

Large-scale population-based studies in medicine are a key resource towards better diagnosis, monitoring, and treatment of diseases. They also serve as enablers of clinical decision support systems, in particular computer-aided diagnosis (CADx) using machine learning (ML). Numerous ML approaches for CADx have been proposed in literature. However, these approaches assume feature-complete data, whic...

Accuracy and deviation analysis of robot-assisted spinal implants: A retrospective overview of 105 cases and preliminary comparison to open freehand surgery in lumbar spondylolisthesis.

BACKGROUND: Whether the accuracy of robot-assisted spinal screw placement is significantly higher than that of freehand and the source of robotic devi...

Automated accurate emotion recognition system using rhythm-specific deep convolutional neural network technique with multi-channel EEG signals.

Emotion is interpreted as a psycho-physiological process, and it is associated with personality, behavior, motivation, and character of a person. The ...

Machine learning of EEG spectra classifies unconsciousness during GABAergic anesthesia.

In current anesthesiology practice, anesthesiologists infer the state of unconsciousness without directly monitoring the brain. Drug- and patient-spec...

Robotic-assisted gait rehabilitation following stroke: a systematic review of current guidelines and practical clinical recommendations.

INTRODUCTION: Stroke is the third leading cause of adult disability worldwide, and lower extremity motor impairment is one of the major determinants o...

An Attention-Based Deep Learning Approach for Sleep Stage Classification With Single-Channel EEG.

Automatic sleep stage mymargin classification is of great importance to measure sleep quality. In this paper, we propose a novel attention-based deep ...

NeuroCrypt: Machine Learning Over Encrypted Distributed Neuroimaging Data.

The field of neuroimaging can greatly benefit from building machine learning models to detect and predict diseases, and discover novel biomarkers, but...

A machine learning approach to screen for preclinical Alzheimer's disease.

Combining multimodal biomarkers could help in the early diagnosis of Alzheimer's disease (AD). We included 304 cognitively normal individuals from the...

Neuromagnetic high frequency spikes are a new and noninvasive biomarker for localization of epileptogenic zones.

OBJECTIVE: One barrier hindering high frequency brain signals (HFBS, >80 Hz) from wide clinical applications is that the brain generates both patholog...

Recent progress of robotic head and neck surgery using a flexible single port robotic system.

We performed robotic neck surgery through a transoral or retroauricular approach (RA) using the DaVinci SP and analyzed our experiences to evaluate th...

White matter hyperintensities segmentation using the ensemble U-Net with multi-scale highlighting foregrounds.

White matter hyperintensities (WMHs) are abnormal signals within the white matter region on the human brain MRI and have been associated with aging pr...

Texture analysis based on U-Net neural network for intracranial hemorrhage identification predicts early enlargement.

BACKGROUND AND OBJECTIVE: Early hemorrhage enlargement in hypertensive cerebral hemorrhage indicates a poor prognosis. This study aims to predict the ...

The Function of Color and Structure Based on EEG Features in Landscape Recognition.

Both color and structure make important contributions to human visual perception, as well as the evaluation of landscape quality and landscape aesthet...

A Pilot Study to Detect Agitation in People Living with Dementia Using Multi-Modal Sensors.

People living with dementia (PLwD) often exhibit behavioral and psychological symptoms, such as episodes of agitation and aggression. Agitated behavio...

Interpreting deep learning models for epileptic seizure detection on EEG signals.

While Deep Learning (DL) is often considered the state-of-the art for Artificial Intel-ligence-based medical decision support, it remains sparsely imp...

Discrepancies in Stroke Distribution and Dataset Origin in Machine Learning for Stroke.

BACKGROUND: Machine learning algorithms depend on accurate and representative datasets for training in order to become valuable clinical tools that ar...

Artificial intelligence in neurodegenerative diseases: A review of available tools with a focus on machine learning techniques.

Neurodegenerative diseases have shown an increasing incidence in the older population in recent years. A significant amount of research has been condu...

A System for Neuromotor Based Rehabilitation on a Passive Robotic Aid.

In the aging world population, the occurrence of neuromotor deficits arising from stroke and other medical conditions is expected to grow, demanding t...

Volume of β-Bursts, But Not Their Rate, Predicts Successful Response Inhibition.

In humans, impaired response inhibition is characteristic of a wide range of psychiatric diseases and of normal aging. It is hypothesized that the rig...