Neurology

Deep Learning Method for Mandibular Canal Segmentation in Dental Cone Beam Computed Tomography Volumes.

Accurate localisation of mandibular canals in lower jaws is important in dental implantology, in which the implant position and dimensions are currently determined manually from 3D CT images by medical experts to avoid damaging the mandibular nerve inside the canal. Here we present a deep learning system for automatic localisation of the mandibular canals by applying a fully convolutional neural n...

High-Resolution Motor State Detection in Parkinson's Disease Using Convolutional Neural Networks.

Patients with advanced Parkinson's disease regularly experience unstable motor states. Objective and reliable monitoring of these fluctuations is an unmet need. We used deep learning to classify motion data from a single wrist-worn IMU sensor recording in unscripted environments. For validation purposes, patients were accompanied by a movement disorder expert, and their motor state was passively e...

Efficacy for Differentiating Nonglaucomatous Versus Glaucomatous Optic Neuropathy Using Deep Learning Systems.

PURPOSE: We sought to assess the performance of deep learning approaches for differentiating nonglaucomatous optic neuropathy with disc pallor (NGON) ...

An artificial intelligence-based EEG algorithm for detection of epileptiform EEG discharges: Validation against the diagnostic gold standard.

OBJECTIVE: To validate an artificial intelligence-based computer algorithm for detection of epileptiform EEG discharges (EDs) and subsequent identific...

Network topology and machine learning analyses reveal microstructural white matter changes underlying Chinese medicine Dengzhan Shengmai treatment on patients with vascular cognitive impairment.

With the increasing incidence of cerebrovascular diseases and dementia, considerable efforts have been made to develop effective treatments on vascula...

Augmented Performance Feedback during Robotic Gait Therapy Results in Moderate Intensity Cardiovascular Exercise in Subacute Stroke.

BACKGROUND: Low cardiovascular fitness is common poststroke. Conventional subacute stroke rehabilitation does not meet Australian National Stroke Guid...

A Novel Soft Robotic Supernumerary Hand for Severely Affected Stroke Patients.

Upper limb functions are severely affected in 23% of the chronic stroke patients, compromising their life quality. To re-enable hand use, providing a ...

Automatic mandibular canal detection using a deep convolutional neural network.

The practicability of deep learning techniques has been demonstrated by their successful implementation in varied fields, including diagnostic imaging...

Scalable diagnostic screening of mild cognitive impairment using AI dialogue agent.

The search for early biomarkers of mild cognitive impairment (MCI) has been central to the Alzheimer's Disease (AD) and dementia research community in...

[Robot therapy with the H2 exoskeleton for gait rehabilitation in patients with incomplete spinal cord injry. A clinical experience].

BACKGROUND AND OBJECTIVE: Robotic exoskeletons have emerged as a promising tool in gait rehabilitation in patients with a spinal cord injury. The aim ...

Artificial Intelligence Mapping of Structure to Function in Glaucoma.

PURPOSE: To develop an artificial intelligence (AI)-based structure-function (SF) map relating retinal nerve fiber layer (RNFL) damage on spectral dom...

EEG based Classification of Long-term Stress Using Psychological Labeling.

Stress research is a rapidly emerging area in the field of electroencephalography (EEG) signal processing. The use of EEG as an objective measure for ...

A propositional AI system for supporting epilepsy diagnosis based on the 2017 epilepsy classification: Illustrated by Dravet syndrome.

PURPOSE: The 2017 epilepsy and seizure diagnosis framework emphasizes epilepsy syndromes and the etiology-based approach. We developed a propositional...

Identification of Methylated Gene Biomarkers in Patients with Alzheimer's Disease Based on Machine Learning.

BACKGROUND: Alzheimer's disease (AD) is a neurodegenerative disorder and characterized by the cognitive impairments. It is essential to identify poten...

Ratchet-integrated pneumatic actuator (RIPA): a large-stroke soft linear actuator inspired by sarcomere muscle contraction.

Pneumatic artificial muscles (PAMs) have a wide range of robotics applications, especially in soft robots, for their ability to generate linear force ...

Robot-Driven Locomotor Perturbations Reveal Synergy-Mediated, Context-Dependent Feedforward and Feedback Mechanisms of Adaptation.

Humans respond to mechanical perturbations that affect their gait by changing their motor control strategy. Previous work indicates that adaptation du...

Alzheimer's disease, mild cognitive impairment, and normal aging distinguished by multi-modal parcellation and machine learning.

A 360-area surface-based cortical parcellation is extended to study mild cognitive impairment (MCI) and Alzheimer's disease (AD) from healthy control ...

Machine Learning Analysis of Digital Clock Drawing Test Performance for Differential Classification of Mild Cognitive Impairment Subtypes Versus Alzheimer's Disease.

OBJECTIVE: To determine how well machine learning algorithms can classify mild cognitive impairment (MCI) subtypes and Alzheimer's disease (AD) using ...

Deep Neural Oracles for Short-Window Optimized Compressed Sensing of Biosignals.

The recovery of sparse signals given their linear mapping on lower-dimensional spaces can be partitioned into a support estimation phase and a coeffic...

Effects of Robot-Assisted Gait Training in Individuals with Spinal Cord Injury: A Meta-analysis.

BACKGROUND: To investigate the effects of robot-assisted gait training (RAGT) on spasticity and pain in people with spinal cord injury (SCI). . Four e...