Latest AI and machine learning research in care of terminally ill / palliative care for healthcare professionals.
Artificial intelligence methods are widely applied to depression recognition and provide an objective solution. Many effective automated methods for detecting depression use facial expressions, which are strong indicators to reflect psychiatric disorders. However, these methods suffer from insufficient representations of depression. To this end, we propose a novel Part-and-Relation Attention Netwo...
In speaker recognition tasks, convolutional neural network (CNN)-based approaches have shown significant success. Modeling the long-term contexts and efficiently aggregating the information are two challenges in speaker recognition, and they have a critical impact on system performance. Previous research has addressed these issues by introducing deeper, wider, and more complex network architecture...
Background Patients presenting to the emergency department (ED) with acute chest pain (ACP) syndrome undergo additional testing to exclude acute coron...
Traumatic brain injury (TBI) engenders traumatic necrosis and penumbra-areas of secondary neural injury which are crucial targets for therapeutic inte...
Markerless estimation of 3D Kinematics has the great potential to clinically diagnose and monitor movement disorders without referrals to expensive mo...
Automated methods for segmentation-based brain volumetry may be confounded by the presence of white matter (WM) lesions, which introduce abnormal inte...
Path planning plays an important role in navigation and motion planning for robotics and automated driving applications. Most existing methods use ite...
An efficient road damage detection system can reduce the risk of road defects to motorists and road maintenance costs to traffic management authoritie...
A non-contrast cranial computer tomography (ncCT) is often employed for the diagnosis of the early stage of the ischemic stroke. However, the number o...
Hierarchical reinforcement learning (HRL) is a promising approach to perform long-horizon goal-reaching tasks by decomposing the goals into subgoals. ...
The prediction of mechanical and dynamical properties of proteins is an important frontier, especially given the greater availability of proteins stru...
An adaptive fuzzy control strategy is proposed for a single-link flexible-joint robotic manipulator (SFRM) with prescribed performance, in which the u...
Abstract-domain adaptation action recognition is a hot research topic in machine learning and some effective approaches have been proposed. However, s...
Human-robot co-transportation allows for a human and a robot to perform an object transportation task cooperatively on a shared environment. This rang...
Effectively predicting protein toxicity plays an essential step in the early stage of protein-based drug discovery, which is of great help to speed up...
Vision-based localization approaches now underpin newly emerging navigation pipelines for myriad use cases, from robotics to assistive technologies. C...
With the rapid development of fault prognostics and health management (PHM) technology, more and more deep learning algorithms have been applied to th...
In this paper, the regulation stability problem of the human arm continuous movement is investigated based on Markovian jumping parameters. In particu...
Due to an increase in the number of disabled people around the world, inclusive solutions are becoming a priority. People with disabilities may encoun...
Significant advances have been achieved in protein structure prediction, especially with the recent development of the AlphaFold2 and the RoseTTAFold ...