Latest AI and machine learning research in geriatrics for healthcare professionals.
BACKGROUND: Identify the influencing factors that respectively affect the differences in cognitive function trajectories between China and the United States, and explore the reasons for gender and transnational differences. METHODS: Five waves of data from the China Health and Retirement Longitudinal Study (CHARLS) and the Health and Retirement Study (HRS) were utilized, and Latent Class Growth Mo...
Aging is a major risk factor for cardiovascular disease, the leading cause of death worldwide, and numerous other diseases, but the mechanisms of these aging-related effects remain elusive. Recent evidence suggests that chronic changes in the microenvironment and local paracrine signaling are major drivers of these effects, but the precise effect of aging on these factors remains understudied. Her...
BACKGROUND: Nasolabial-fold (NLF) severity is a key indicator of facial aging and a frequent target in aesthetic treatments. The Wrinkle Severity Rati...
To construct an efficient predictive model for post-lung cancer resection delirium (POD) using artificial intelligence, with a focus on leveraging syn...
Multimodal image fusion and object detection significantly enhance detection accuracy and robustness in complex environments, which is crucial for aut...
RATIONALE AND OBJECTIVES: With the emergence of disease-modifying therapies, precise staging of dementia is urgent. This study aimed to develop a mach...
Aging and age-related diseases are a major public health concern, driving interest in anti-aging research. While small molecules and natural compounds...
BackgroundSubjective cognitive decline (SCD) represents the first early symptomatic stage of Alzheimer's disease (AD).ObjectiveWe aimed to investigate...
BACKGROUND: As artificial intelligence (AI) becomes increasingly embedded in clinical decision-making and preventive care, it is urgent to address eth...
BACKGROUND: Assistive robotics for helping older people live well and stay independent has, to date, failed to fulfill its promise: there are few assi...
To determine whether there are radiomic ultrasound features of early pregnancy when viability is unknown, which in combination with clinical features,...
Machine-learning-based interatomic potentials are widely employed in atomistic simulations, but they struggle to capture long-range electrostatic corr...
Sarcopenia, the gradual loss of skeletal muscle mass, strength, and function, is a growing concern in aging populations. Early detection is vital to r...
Biological proteins play a crucial role at the intersection of oral health and neuroscience, offering promising opportunities for improved diagnosis, ...
BACKGROUND: Alzheimer's Disease (AD) and FrontoTemporal Dementia (FTD) are dementia conditions that often overlap clinically, leading to misdiagnoses....
AIM: This study aimed to develop a machine learning (ML)-assisted model to predict the risk of upstaging (subsequent higher stage on repeat pathology)...
OBJECTIVES: Intracranial hemorrhage (ICH) is a time-critical neurological emergency in which rapid CT-based assessment directly informs treatment deci...
ETHNOPHARMACOLOGICAL RELEVANCE: According to the Traditional Chinese Medicine (TCM) tenet that "internal imbalances manifest externally," skin aging r...
OBJECTIVE: Accurate prediction of survival outcome is essential for early intervention and treatment optimization. This study aimed to develop a model...
OBJECTIVES: The frailty phenotype has limitations in capturing the biological heterogeneity of the condition. Our study identified subtypes of frailty...