Latest AI and machine learning research in geriatrics for healthcare professionals.
Given that mobile soft robots are adaptable to the environment, they are always tethered with slow locomotion speed. Compared with other types of mobile robots, mobile soft robots may be more suitable for rescuing tasks, accompanying elderly people, and being used as a safe toy for children. However, the infinite freedom of soft robots increases the difficulty of precision control. In addition, th...
Machine learning (ML) methods have the potential to automate clinical EEG analysis. They can be categorized into feature-based (with handcrafted features), and end-to-end approaches (with learned features). Previous studies on EEG pathology decoding have typically analyzed a limited number of features, decoders, or both. For a I) more elaborate feature-based EEG analysis, and II) in-depth comparis...
The social impact of robotics applied to domains such as education, religion, nursing, and therapy across the world depends on the level of technology...
BACKGROUND: The number of applications of deep learning algorithms in bioinformatics is increasing as they usually achieve superior performance over c...
Traditional neuroimage analysis pipelines involve computationally intensive, time-consuming optimization steps, and thus, do not scale well to large c...
INTRODUCTION: Demographic changes in society and fewer personnel working in healthcare services have resulted in an increase in the speed of developme...
Many neurological diseases and delineating pathological regions have been analyzed, and the anatomical structure of the brain researched with the aid ...
In this paper, we embed two types of attention modules in the dilated fully convolutional network (FCN) to solve biomedical image segmentation tasks e...
Alzheimer's disease (AD) is the most common cause of dementia and a progressive neurodegenerative condition, characterized by a decline in cognitive f...
The topic of sparse representation of samples in high dimensional spaces has attracted growing interest during the past decade. In this work, we devel...
The prediction of Mild Cognitive Impairment (MCI) patients who are at higher risk converting to Alzheimer's Disease (AD) is critical for effective int...
Subtle changes in white matter (WM) microstructure have been associated with normal aging and neurodegeneration. To study these associations in more d...
This study aims to develop a prototype of an autonomous robotic device to assist the locomotion of the elderly in urban environments. Among the achiev...
Tracklet association methods learn the cross camera retrieval ability though associating underlying cross camera positive samples, which have proven t...
PURPOSE: The purpose of this study was to build and train a deep convolutional neural networks (CNN) algorithm to segment muscular body mass (MBM) to ...
Disruptions of brain metabolism are considered integral to the pathogenesis of dementia, but thus far little is known of how dementia with Lewy bodies...
Health and social care services are crucial to old people. The provision of services to the elderly with care needs requires more accurate predictions...
Pressure injuries represent a major concern in many nations. These wounds result from prolonged pressure on the skin, which mainly occur among elderly...
Predicting biomedical outcomes from Magnetoencephalography and Electroencephalography (M/EEG) is central to applications like decoding, brain-computer...
Accurate assessment of renal function is essential in hospitalized elderly patients. Few studies have examined the accuracy of Cockcroft-Gault (C-G) ...