AIMC Topic: Humans
Showing 66051 to 66060 of 95995 articles
The feasibility of using robotic technology to quantify sensory, motor, and cognitive impairments associated with ALS.
Amyotrophic lateral sclerosis & frontotemporal degeneration
Jan 27, 2019
OBJECTIVE: We used the KINARM robot to quantify impairments in cognitive and upper-limb sensorimotor performance in a cohort of people with amyotrophic lateral sclerosis (ALS). We sought to study the feasibility of using this technology for ALS resea...
Health-Aware Model-Predictive Control of a Cooperative AGV-Based Production System.
Sensors (Basel, Switzerland)
Jan 27, 2019
In the paper, a new scheduling strategy for assembly systems consisting of cooperating Automated Guided Vehicles (AGVs) based on their remaining operational time is developed. The operational time is associated with state of charge and state of healt...
Control of a Humanoid NAO Robot by an Adaptive Bioinspired Cerebellar Module in 3D Motion Tasks.
Computational intelligence and neuroscience
Jan 27, 2019
A bioinspired adaptive model, developed by means of a spiking neural network made of thousands of artificial neurons, has been leveraged to control a humanoid NAO robot in real time. The learning properties of the system have been challenged in a cla...
A fast kernel extreme learning machine based on conjugate gradient.
Network (Bristol, England)
Jan 27, 2019
Kernel extreme learning machine (KELM) introduces kernel leaning into extreme learning machine (ELM) in order to improve the generalization ability and stability. But the Penalty parameter in KELM is randomly set and it has a strong impact on the per...
A Deep Learning Algorithm to Quantify Neuroretinal Rim Loss From Optic Disc Photographs.
American journal of ophthalmology
Jan 26, 2019
PURPOSE: To train a deep learning (DL) algorithm that quantifies glaucomatous neuroretinal damage on fundus photographs using the minimum rim width relative to Bruch membrane opening (BMO-MRW) from spectral-domain optical coherence tomography (SDOCT)...
Visual Field Tests
Optic Nerve Diseases
Photography
Glaucoma, Open-Angle
Optic Disk
Retinal Ganglion Cells
Visual Fields
Bruch Membrane
Male
Middle Aged
Deep Learning
Tomography, Optical Coherence
Nerve Fibers
Vision Disorders
Area Under Curve
Aged
Aged, 80 and over
Cross-Sectional Studies
Intraocular Pressure
Algorithms
Retrospective Studies
Female
Humans
RNN-based longitudinal analysis for diagnosis of Alzheimer's disease.
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Jan 26, 2019
Alzheimer's disease (AD) is an irreversible neurodegenerative disorder with progressive impairment of memory and other mental functions. Magnetic resonance images (MRI) have been widely used as an important imaging modality of brain for AD diagnosis ...
A gentle introduction to deep learning in medical image processing.
Zeitschrift fur medizinische Physik
Jan 25, 2019
This paper tries to give a gentle introduction to deep learning in medical image processing, proceeding from theoretical foundations to applications. We first discuss general reasons for the popularity of deep learning, including several major breakt...
Walking Imagery Evaluation in Brain Computer Interfaces via a Multi-View Multi-Level Deep Polynomial Network.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Jan 25, 2019
Brain-computer interfaces based on motor imagery (MI) have been widely used to support the rehabilitation of motor functions of the upper limbs rather than lower limbs. This is probably because it is more difficult to detect the brain activities of l...
Prediction of skin dose in low-kV intraoperative radiotherapy using machine learning models trained on results of in vivo dosimetry.
Medical physics
Jan 25, 2019
PURPOSE: The purpose of this study was to implement a machine learning model to predict skin dose from targeted intraoperative (TARGIT) treatment resulting in timely adoption of strategies to limit excessive skin dose.
Predicting Future Driving Risk of Crash-Involved Drivers Based on a Systematic Machine Learning Framework.
International journal of environmental research and public health
Jan 25, 2019
The objective of this paper is to predict the future driving risk of crash-involved drivers in Kunshan, China. A systematic machine learning framework is proposed to deal with three critical technical issues: 1. defining driving risk; 2. developing r...
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