Latest AI and machine learning research in geriatrics for healthcare professionals.
Accurate and early diagnosis of Alzheimer's disease (AD) plays important role for patient care and d...
BACKGROUND: Existing screening tools for early detection of autism are expensive, cumbersome, time- ...
The differential diagnosis of atypical dementia remains difficult. The use of positron emission tomo...
MOTIVATION: The use of drug combinations, termed polypharmacy, is common to treat patients with comp...
Electroencephalogram (EEG) signal based early diagnosis of Alzheimer's Disease (AD), especially a di...
Alzheimer's disease (AD), a progressive brain disorder, is the most common neurodegenerative disease...
Human activity recognition (HAR) is an important component in health-care systems. For example, it c...
The population in advanced countries is rapidly aging, and these countries are faced with various is...
This paper presents a physiological monitoring system for assistive robots using a thermal camera. I...
Thanks to deep convolutional neural networks (CNNs), Brain Tumor Segmentation (BTS) has made great p...
PURPOSE OF REVIEW: To review current practices and technologies within the scope of "Big Data" that ...
Automated methods for detecting clinically significant (CS) prostate cancer (PCa) in multi-parameter...
This work was part of a National Institute for Health Research participatory action research and pra...
In 2014, we reported a model for donor-recipient (D-R) matching in liver transplantation (LT) based ...
BACKGROUND: Available therapies for Alzheimer's disease (AD) can only alleviate and delay the advanc...
Naodesheng (NDS) formula, which consists of Rhizoma Chuanxiong, Lobed Kudzuvine, Carthamus tinctoriu...
Patient data in clinical research often includes large amounts of structured information, such as ne...
In this study, we aimed to teach elementary school students how to practically deal with elderly peo...
Digitalisation of health care for the purpose of medical documentation lead to huge amounts of data,...
The use of electronic health records for risk prediction models requires a sufficient quality of inp...
We applied machine learning techniques to a community-based behavioral dataset to build prediction m...