BACKGROUND: Various technologies have been developed to improve hand hygiene (HH) compliance in inpatient settings; however, little is known about the feasibility of machine learning technology for this purpose in outpatient clinics.
PURPOSE: To develop a super-resolution technique using convolutional neural networks for generating thin-slice knee MR images from thicker input slices, and compare this method with alternative through-plane interpolation methods.
European journal of paediatric neurology : EJPN : official journal of the European Paediatric Neurology Society
Mar 23, 2018
Robotically-driven orthoses (RDO) are promising for treating gait impairment in children with hemiplegia after acquired brain injury (ABI). Despite this, existing literature on the employment of RDO in ABI is scanty, and cohorts' age spans throughout...
Journal of voice : official journal of the Voice Foundation
Mar 19, 2018
OBJECTIVES: Computerized detection of voice disorders has attracted considerable academic and clinical interest in the hope of providing an effective screening method for voice diseases before endoscopic confirmation. This study proposes a deep-learn...
European journal of physical and rehabilitation medicine
Mar 7, 2018
BACKGROUND: Wearable robots are people-oriented robots designed to be worn all day, thus helping in the daily activities. They can assist in walking, running, jumping higher or even lifting objects too heavy in normal conditions.
In the last decade robotic devices have been applied in rehabilitation to overcome walking disability in neurologic diseases with promising results. Robot assisted gait training (RAGT) using the Lokomat seems not only to improve gait parameters but a...
BACKGROUND: Socially assistive robots are being developed for patients to help manage chronic health conditions such as chronic obstructive pulmonary disease (COPD). Adherence to medication and availability of rehabilitation are suboptimal in this pa...
We assessed the feasibility of a data-driven imaging biomarker based on weakly supervised learning (DIB; an imaging biomarker derived from large-scale medical image data with deep learning technology) in mammography (DIB-MG). A total of 29,107 digita...