Neurology

Machine learning powered tools for automated analysis of muscle sympathetic nerve activity recordings.

Automated analysis and quantification of physiological signals in clinical practice and medical research can reduce manual labor, increase efficiency, and provide more objective, reproducible results. To build a novel platform for the analysis of muscle sympathetic nerve activity (MSNA), we employed state-of-the-art data processing and machine learning applications. Data processing methods for int...

Towards realizing the vision of precision medicine: AI based prediction of clinical drug response.

Accurate and individualized prediction of response to therapies is central to precision medicine. However, because of the generally complex and multifaceted nature of clinical drug response, realizing this vision is highly challenging, requiring integrating different data types from the same individual into one prediction model. We used the anti-epileptic drug brivaracetam as a case study and comb...

Organizing principles of the C. elegans contactome.

Two recent studies published in Nature generate and analyze, for the first time, the network of ∼100,000 membrane contacts between neurons in the C. e...

Brief Report: Neuroimaging Endophenotypes of Social Robotic Applications in Autism Spectrum Disorder.

A plethora of neuroimaging studies have focused on the discovery of potential neuroendophenotypes useful to understand the etiopathogenesis of autism ...

Introduction. Neurosurgical management of stroke, organization of stroke management, and artificial intelligence applications.

Individualized Glaucoma Change Detection Using Deep Learning Auto Encoder-Based Regions of Interest.

PURPOSE: To compare change over time in eye-specific optical coherence tomography (OCT) retinal nerve fiber layer (RNFL)-based region-of-interest (ROI...

Deep Learning-Based Retinal Nerve Fiber Layer Thickness Measurement of Murine Eyes.

PURPOSE: To design a robust and automated estimation method for measuring the retinal nerve fiber layer (RNFL) thickness using spectral domain optical...

[Using electroencephalogram for emotion recognition based on filter-bank long short-term memory networks].

Emotion plays an important role in people's cognition and communication. By analyzing electroencephalogram (EEG) signals to identify internal emotions...

A data-driven approach to post-stroke aphasia classification and lesion-based prediction.

Aphasia is an acquired impairment in the production or comprehension of language, typically caused by left hemisphere stroke. The subtyping framework ...

U-Limb: A multi-modal, multi-center database on arm motion control in healthy and post-stroke conditions.

BACKGROUND: Shedding light on the neuroscientific mechanisms of human upper limb motor control, in both healthy and disease conditions (e.g., after a ...

Present and Future Spinal Robotic and Enabling Technologies.

Enabling technologies include surgical planning software, computer-assisted navigation, intraoperative three-dimensional (3D) imaging, and robotic sys...

Accelerated Aging of the Amygdala in Alcohol Use Disorders: Relevance to the Dark Side of Addiction.

Here we assessed changes in subcortical volumes in alcohol use disorder (AUD). A simple morphometry-based classifier (MC) was developed to identify su...

[Clinical and morphological assessment of the results of a standard robot-assisted nerve-sparing radical prostatectomy and with the use of Retzius-sparing technique].

OBJECTIVE: To compare the perioperative, functional, clinical and morphological results of a standard robot-assisted nerve-sparing radical prostatecto...

Emotion Recognition Using Spectral Feature from Facial Electromygraphy Signals for Human-Machine Interface.

Recognition of the emotions demonstrated by human beings plays a crucial role in healthcare and human-machine interface. This paper reports an attempt...

The Path to Surgical Robotics in Neurosurgery.

Robotic systems may help efficiently execute complicated tasks that require a high degree of accuracy, and this, in large part, explains why robotics ...

Combining In Vivo Corneal Confocal Microscopy With Deep Learning-Based Analysis Reveals Sensory Nerve Fiber Loss in Acute Simian Immunodeficiency Virus Infection.

PURPOSE: To characterize corneal subbasal nerve plexus features of normal and simian immunodeficiency virus (SIV)-infected macaques by combining in vi...

Robot-induced hallucinations in Parkinson's disease depend on altered sensorimotor processing in fronto-temporal network.

Hallucinations in Parkinson's disease (PD) are disturbing and frequent non-motor symptoms and constitute a major risk factor for psychosis and dementi...

Dual high-stroke and high-work capacity artificial muscles inspired by DNA supercoiling.

Powering miniature robots using actuating materials that mimic skeletal muscle is attractive because conventional mechanical drive systems cannot be r...

[Complications of Da Vinci robot thyroid surgery by bilateral axillo-breast approach].

To evaluate the complications of Da Vinci robotic thyroid surgery by bilateral axillo-breast approach. A retrospective analysis of complications was...

Deep Learning on Conventional Magnetic Resonance Imaging Improves the Diagnosis of Multiple Sclerosis Mimics.

OBJECTIVES: The aims of this study were to present a deep learning approach for the automated classification of multiple sclerosis and its mimics and ...