Latest AI and machine learning research in geriatrics for healthcare professionals.
Osteoporosis is treatable but often overlooked in clinical practice. We aimed to construct predictio...
This epidemiological study aimed to develop an X-AI that could explain groups with a high anxiety di...
BACKGROUND & AIMS: Body composition analysis on CT images is a valuable tool for sarcopenia assessme...
BACKGROUND: In medical diagnosis of brain, the role of multi-modal medical image fusion is becoming ...
OBJECTIVES: Alzheimer's disease (AD) is the most prevalent neurodegenerative disorder and the most c...
The field of robot-assisted physical rehabilitation and robotics technology for providing support to...
Background and Objective Electrocardiogram (ECG) quality assessment is significant for automatic dia...
The central challenge in automated synthesis planning is to be able to generate and predict outcomes...
Ubiquitous health management (UHM) is vital in the aging society. The UHM services with artificial i...
While many diseases of aging have been linked to the immunological system, immune metrics capable of...
Fall detection (FD) systems are important assistive technologies for healthcare that can detect emer...
Traditional Chinese Medicine (TCM) is a well-established medical system with a long history. Current...
In this study, algorithms to detect post-falls were evaluated using the cross-dataset according to f...
BACKGROUND: Radical cystectomy (RC) is the standard treatment for bladder cancer, but the safety and...
We consider a human-in-the-loop scenario in the context of low-shot learning. Our approach was inspi...
There is currently no consensus among plastic surgeons regarding the optimal infection prophylaxis ...
The disease Alzheimer is an irrepressible neurologicalbrain disorder. Earlier detection and proper t...
Osteoporosis is a global health problem for ageing populations. The goals of osteoporosis treatment ...
Alzheimer's disease (AD) is a neurodegenerative disorder causing 70% of dementia cases. However, the...
Edge-cloud collaborative inference can significantly reduce the delay of a deep neural network (DNN)...
Deep learning algorithms for left ventricle (LV) segmentation are prone to bias towards the training...