Latest AI and machine learning research in geriatrics for healthcare professionals.
The active assembly of molecules by nanorobots has advanced greatly since “molecular manufacturing”—that is, the use of nanoscale tools to build molecular structures—was proposed. In contrast to a catalyst, which accelerates a reaction by smoothing the potential energy surface along the reaction coordinate, molecular machines expend energy to accelerate a reaction relative to the baseline provided...
Depression is one of the most common mental health problems in middle-aged and elderly people. The establishment of risk factor-based depression risk assessment model is conducive to early detection and early treatment of high-risk groups of depression. Five machine learning models (logistic regression (LR); back propagation (BP); random forest (RF); support vector machines (SVM); category boostin...
COVID-19 has claimed several human lives to this date. People are dying not only because of physical infection of the virus but also because of mental...
BACKGROUND: Recently, machine learning-based ligand activity prediction methods have been greatly improved. However, if known active compounds of a ta...
It is widely thought that individuals age at different rates. A method that measures "physiological age" or physiological aging rate independent of ch...
Sustained attention is essential for older adults to maintain an active lifestyle, and the deficiency of this function is often associated with health...
Falls are a major cause of morbidity and mortality in neurological disorders. Technical means of detecting falls are of high interest as they enable r...
Aging refers to progressive physiological changes in a cell, an organ, or the whole body of an individual, over time. Aging-related diseases are highl...
BACKGROUND: Sarcopenia is defined as muscle wasting, characterized by a progressive loss of muscle mass and function due to ageing. Diagnosis of sarco...
OBJECTIVE: Gabapentinoids (GPT) are reported to be increasingly misused by opioid- and polydrug-users, but the addictive potential of GPT outside of t...
Structural magnetic resonance imaging (sMRI) can capture the spatial patterns of brain atrophy in Alzheimer's disease (AD) and incipient dementia. Rec...
Parkinson's disease (PD), Alzheimer's disease (AD) are common neurodegenerative disease, while mild cognitive impairment (MCI) may be happened in the...
Healthy aging is a new challenge for the world. Therefore, health literacy education is a key issue in the current health care field. This research ha...
In this unprecedented era of the overwhelming volume of medical data, machine learning can be a promising tool that may shed light on an individualize...
The large number of poststroke recovery patients poses a burden on rehabilitation centers, hospitals, and physiotherapists. The advent of rehabilitati...
High accuracy has been reported in deep learning classification for amyloid brain scans, an important factor in Alzheimer's disease diagnosis. However...
The cognitive approach to psychotherapy aims to change patients' maladaptive schemas, that is, overly negative views on themselves, the world, or the ...
The increasingly ageing population and the tendency to live alone have led science and engineering researchers to search for health care solutions. In...
OBJECTIVE: To explore the application value of magnetic resonance spectroscopy (MRS) and GSI-energy spectrum electronic computed tomography (CT) medic...
Cognitive workload is a crucial factor in tasks involving dynamic decision-making and other real-time and high-risk situations. Neuroimaging technique...