Latest AI and machine learning research in staffing & scheduling for healthcare professionals.
Labeling training data is increasingly the largest bottleneck in deploying machine learning systems....
Untethered small-scale robots have great potential for biomedical applications. However, critical ba...
BACKGROUND: Accurate estimation of operative case-time duration is critical for optimizing operating...
PURPOSE: This trial aimed to validate the effectiveness of using the Gait Exercise Assist Robot (GEA...
This study investigated to what extent multimodal data can be used to detect mistakes during Cardiop...
Technologies and methods to speed up the production of systematic reviews by reducing the manual lab...
Robot-assisted gait training following acute stroke could allow patients with severe disability to r...
INTRODUCTION: Robot-assisted therapy for the upper limb (RT-UL) is an emerging form of intervention ...
In this paper, a hybrid deep neural network scheduler (HDNNS) is proposed to solve job-shop scheduli...
To conduct a survey on the research and development of cable-driven rehabilitation devices (CDRDs)....
Building spiking neural networks (SNNs) based on biological synaptic plasticities holds a promising ...
BackgroundManagement of thyroid nodules may be inconsistent between different observers and time con...
Different adaptation rates have been reported in studies involving ankle exoskeletons designed to re...
OBJECTIVES: To provide proof-of-concept for a protocol applying a strategy of personalized mechanica...
We propose a new deep learning approach for medical imaging that copes with the problem of a small t...
The aim of this work was to develop a PAT platform consisting of four complementary instruments for ...
Genetic polymorphisms are mostly associated with inherited diseases, detecting and analyzing the bio...
BACKGROUND: Basecalling, the computational process of translating raw electrical signal to nucleotid...
BACKGROUND: Body weight supported treadmill training (BWSTT) is a frequently used approach for resto...
BACKGROUND: In recent months, multiple publications have demonstrated the use of convolutional neura...
Recent studies have demonstrated the effectiveness of supervised learning in spiking neural networks...