Neurology

Using deep learning models to analyze the cerebral edema complication caused by radiotherapy in patients with intracranial tumor.

Using deep learning models to analyze patients with intracranial tumors, to study the image segmentation and standard results by clinical depiction complications of cerebral edema after receiving radiotherapy. In this study, patients with intracranial tumors receiving computer knife (CyberKnife M6) stereotactic radiosurgery were followed using the treatment planning system (MultiPlan 5.1.3) to obt...

A Case Study of Upper Limb Robotic-Assisted Therapy Using the Track-Hold Device.

The Track-Hold System (THS) project, developed in a healthcare facility and therefore in a controlled and protected healthcare environment, contributes to the more general and broad context of Robotic-Assisted Therapy (RAT). RAT represents an advanced and innovative rehabilitation method, both motor and cognitive, and uses active, passive, and facilitating robotic devices. RAT devices can be equip...

Cross-Task Cognitive Workload Recognition Based on EEG and Domain Adaptation.

Cognitive workload recognition is pivotal to maintain the operator's health and prevent accidents in the human-robot interaction condition. So far, th...

A simulation study to investigate the use of concentric tube robots for epilepsy surgery.

PURPOSE: Patients with pharmacoresistant refractory epilepsy may require epilepsy surgery to prevent future seizure occurrences. Conventional surgery ...

Stretchable Neuromorphic Transistor That Combines Multisensing and Information Processing for Epidermal Gesture Recognition.

We fabricated a nanowire-channel intrinsically stretchable neuromorphic transistor (NISNT) that perceives both tactile and visual information and emul...

Glaucoma disease diagnosis with an artificial algae-based deep learning algorithm.

Glaucoma disease is optic neuropathy; in glaucoma, the optic nerve is damaged because the long duration of intraocular pressure can be caused blindnes...

Intelligent assistive technology devices for persons with dementia: A scoping review.

Assistive technology (AT) with context-aware computing and artificial intelligence capabilities can be applied to address cognitive and communication ...

A gradient-based automatic optimization CNN framework for EEG state recognition.

. The electroencephalogram (EEG) signal, as a data carrier that can contain a large amount of information about the human brain in different states, i...

Ontology-based identification and prioritization of candidate drugs for epilepsy from literature.

BACKGROUND: Drug repurposing can improve the return of investment as it finds new uses for existing drugs. Literature-based analyses exploit factual k...

DOTA: Deep Learning Optimal Transport Approach to Advance Drug Repositioning for Alzheimer's Disease.

Alzheimer's disease (AD) is the leading cause of age-related dementia, affecting over 5 million people in the United States and incurring a substantia...

An Exploration: Alzheimer's Disease Classification Based on Convolutional Neural Network.

Alzheimer's disease (AD) is the most generally known neurodegenerative disorder, leading to a steady deterioration in cognitive ability. Deep learning...

The effects of temperature on the dynamics of the biological neural network.

The nerve cells are responsible for transmitting messages through the action potential, which generates electrical stimulation. One of the methods and...

Three-Dimensional Carpal Arch Morphology Using Robot-Assisted Ultrasonography.

OBJECTIVE: The morphology of the carpal arch implicates the available space for the median nerve within the carpal tunnel. The purposes of this study ...

Probabilistic Model-Based Learning Control of a Soft Pneumatic Glove for Hand Rehabilitation.

OBJECTIVE: Stroke survivors are usually unable to perform activities of daily living (ADL) independently due to loss of hand functions. Soft pneumatic...

Review on Epileptic Seizure Prediction: Machine Learning and Deep Learning Approaches.

Epileptic seizures occur due to brain abnormalities that can indirectly affect patient's health. It occurs abruptly without any symptoms and thus incr...

Artificial intelligence for medical image analysis in epilepsy.

Given improvements in computing power, artificial intelligence (AI) with deep learning has emerged as the state-of-the art method for the analysis of ...

Bony fixation in the era of spinal robotics: A systematic review and meta-analysis.

BACKGROUND: Accurate spinal screw placement in spinal instrumentation is of utmost importance to avoid injury to surrounding neurovascular structures....

Ultrasound Image-Guided Nerve Block Combined with General Anesthesia under an Artificial Intelligence Algorithm on Patients Undergoing Radical Gastrectomy for Gastric Cancer during and after Operation.

This study was aimed at investigating the location of gastric cancer by using a gastroscope image based on an artificial intelligence algorithm for ga...

A review of motor neural system robotic modeling approaches and instruments.

In this review, we are considering an actively developing tool in neuroscience-robotic modeling. The new perspective and existing application fields, ...

Automated grading of enlarged perivascular spaces in clinical imaging data of an acute stroke cohort using an interpretable, 3D deep learning framework.

Enlarged perivascular spaces (EPVS), specifically in stroke patients, has been shown to strongly correlate with other measures of small vessel disease...