Latest AI and machine learning research in geriatrics for healthcare professionals.
BACKGROUND: The mechanism of palmitoylation in the pathogenesis of Alzheimer's disease (AD) remains ...
In image segmentation for medical image analysis, effective upsampling is crucial for recovering spa...
Existing dementia prediction models using non-neuroimaging clinical measures have been limited in th...
BACKGROUND: Intracerebral amyloid β (Aβ) accumulation is considered the initial observable event in ...
Alzheimer's disease (AD) is characterized as a neurodegenerative disorder that is caused by plaque f...
When infants are admitted to the hospital with skull fractures, providers must distinguish between c...
OBJECTIVES: The future emergence of disease-modifying treatments for dementia highlights the urgent ...
Integrating 3D magnetic resonance imaging (MRI) with machine learning has shown promising results in...
BACKGROUND: The two most commonly used methods to identify frailty are the frailty phenotype and the...
UNLABELLED: This study utilized deep learning for bone mineral density (BMD) prediction and classifi...
OBJECTIVE: The objective of this study was to develop and validate a clinically applicable nomogram ...
BACKGROUND: Alzheimer's disease (AD) is a common neurodegenerative disorder worldwide and the using ...
Osteoporotic femoral neck fractures (OFNFs) pose a significant orthopedic challenge in the elderly p...
BACKGROUND: Alzheimer's disease (AD), the most prevalent form of dementia, remains enigmatic in its ...
BACKGROUND: Alzheimer's disease (AD) is a neurodegenerative disorder. There are no drugs and methods...
BACKGROUND AND AIM: Changes in cognitive function are commonly associated with aging in patients wit...
Microplastics (MPs) easily migrate into deeper soil layers, posing potential risks to subterranean h...
AIM: Pre-injury frailty has been investigated as a tool to predict outcomes of older trauma patients...
OBJECTIVE: To test whether an artificial intelligence (AI) deep neural network (DNN)-derived analysi...
Time-to-event data are very common in medical applications. Regression models have been developed on...
PURPOSE: We examined whether end-to-end deep-learning models could detect moderate (≥50%) or severe ...