Expert review of molecular diagnostics
Jul 1, 2025
INTRODUCTION: Accurate prediction of short-term mortality is crucial for optimizing clinical prognosis and providing treatment decisions. Conventional metrics, including physiological indicators, laboratory indexes and scoring systems, suffer from li...
As the older adult population continues to expand, the demands on the healthcare system intensifies, necessitating the development of technologies that effectively accommodate the requirements of older adults. While Artificial Intelligence (AI) syste...
BACKGROUND: Monitoring intrinsic capacity and implementing appropriate interventions can support healthy aging. There are, though, few tools available for predicting decline in intrinsic capacity among older adults. This study aimed to develop and va...
Archives of gerontology and geriatrics
Jul 1, 2025
BACKGROUND: Frailty, a significant predictor of adverse health outcomes, has become a focal point of research, particularly with the advent of artificial intelligence (AI) technologies. This study aimed to provide a comprehensive bibliometric analysi...
The journals of gerontology. Series A, Biological sciences and medical sciences
Jun 10, 2025
BACKGROUND: As the global population ages healthcare challenges are escalating. Frailty, a clinical syndrome characterized by decreased reserve and resilience to stressors, is critically linked to adverse health outcomes in older adults. However, art...
The journals of gerontology. Series B, Psychological sciences and social sciences
Jun 10, 2025
The National Institute on Aging (NIA) is at the forefront of leveraging advances in artificial intelligence (AI) to better understanding of aging and the diagnosis and treatment of Alzheimer's Disease (AD) and Alzheimer's disease-related dementias (A...
The journals of gerontology. Series B, Psychological sciences and social sciences
Jun 10, 2025
OBJECTIVES: Confronted with shrinking social networks, older adults exhibit individual differences in social adaptability, reflected as socially resilient versus socially vulnerable. The purpose of this study was to examine key features that reflect ...
"Predicted brain age" refers to a biomarker of structural brain health derived from machine learning analysis of T1-weighted brain magnetic resonance (MR) images. A range of machine learning methods have been used to predict brain age, with convoluti...
The brain undergoes complex but normal structural changes during the aging process in healthy adults, whereas deviations from the normal aging patterns of the brain can be indicative of various conditions as well as an increased risk for the developm...
Deep learning frameworks utilizing convolutional neural networks (CNNs) have frequently been used for brain age prediction and have achieved outstanding performance. Nevertheless, deep learning remains a black box as it is hard to interpret which bra...
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