Latest AI and machine learning research in geriatrics for healthcare professionals.
BACKGROUND: Alzheimer's Disease (AD) is a degenerative brain disorder that often occurs in people over 65Â years old. As advanced AD is difficult to manage, accurate diagnosis of the disorder is critical. Previous studies have revealed effective deep learning methods of classification. However, deep learning methods require a large number of image datasets. Moreover, medical images are affected by ...
Functional MRI (fMRI) is a prominent imaging technique to probe brain function, however, a substantial proportion of noise from multiple sources influences the reliability and reproducibility of fMRI data analysis and limits its clinical applications. Extensive effort has been devoted to improving fMRI data quality, but in the last two decades, there is no consensus reached which technique is more...
Speech is controlled by axial neuromotor systems, therefore, it is highly sensitive to the effects of neurodegenerative illnesses such as Parkinson's ...
The benefits of automatic identification technologies in healthcare have been largely recognized. Nevertheless, unlocking their potential to support t...
A machine learning (ML) system is able to construct algorithms to continue improving predictions and generate automated knowledge through data-driven...
BACKGROUND: Paro and other robot animals can improve wellbeing for older adults and people with dementia, through reducing depression, agitation and m...
Artificial intelligence (AI) will transform every step in the imaging value chain, including interpretive and noninterpretive components. Radiologists...
BACKGROUND: As the population ages, the incidence of traumatic falls has been increasing. We hypothesize that a machine learning algorithm can more ac...
OBJECTIVE: Efficient prediction of the progression of mild cognitive impairment (MCI) to Alzheimer's disease (AD) is important for the early intervent...
Cytometry technologies are essential tools for immunology research, providing high-throughput measurements of the immune cells at the single-cell leve...
BACKGROUND: Populations are aging at an alarming rate in many countries around the world. There has been not only a decrease in the number of births a...
BACKGROUND: Sarcopenia, defined as the age-associated loss of muscle mass and strength, can be effectively mitigated through resistance-based physical...
BACKGROUND: Sarcopenia has been confirmed as a poor prognostic indicator of lung cancer. However, the lack of abdominal computed tomography (CT) hinde...
INTRODUCTION: Alzheimer's disease (AD) is a complex and heterogeneous disease that affects neuronal cells over time and it is prevalent among all neur...
Osteoporosis is a prevalent but underdiagnosed condition. As compared to dual-energy X-ray absorptiometry (DXA) measures, we aimed to develop a deep c...
BACKGROUND: Sarcopenia, a syndrome characterized by the loss of skeletal muscle mass, has attracted attention in the field of oncology, as it reflects...
The Alzheimer's Disease Neuroimaging (ADNI) database is an expansive undertaking by government, academia, and industry to pool resources and data on s...
The past decade in rheumatology has seen tremendous innovation in digital health technologies, including the electronic health record, virtual visits,...
OBJECTIVE: The aim of this research is to identify the stage of Alzheimer's Disease (AD) patients through the use of mobility data and deep learning m...
The application of ultrasound (US) imaging in orthopedic surgery has always been a research direction. However, the various problems of US imaging hin...