Latest AI and machine learning research in geriatrics for healthcare professionals.
BACKGROUND AND OBJECTIVE: The unloaded cardiac geometry, representing the zero-stress and zero-strain reference state of the heart, is fundamental for personalized biomechanical modeling of cardiac function. However, this state cannot be directly observed in vivo, as clinical imaging only captures pressure-loaded geometries such as those at end-diastole. Traditional inverse finite element solvers ...
OBJECTIVES: Amyloid-β (Aβ) PET is crucial for diagnosing and monitoring Alzheimer's disease (AD), but its high cost and radiation exposure limit its use. Deep learning techniques make it possible to generate PET from structured MRI data. In this study, we built a deep learning model to generate 3D synthetic Aβ PET images from structural MRI. MATERIALS AND METHODS: The generative adversarial networ...
BACKGROUND: Accurate assessment of 90-day functional outcomes after anterior circulation large vessel occlusion (LVO) stroke remains challenging. Conv...
This study presents Latent Diffusion Autoencoder (LDAE), a novel encoder-decoder diffusion-based framework for efficient and meaningful unsupervised l...
Chronic pain is linked to accelerated brain aging, often measured through the brain-age gap (BAG), the difference between chronological age and neuroi...
Alzheimer's disease (AD) -the most common form of dementia- begins with mild memory loss and gradually progresses, eventually resulting in a generaliz...
Deep learning algorithms optimize data by enhancing resolution and suppressing noise associated with biological knowledge. The root issue is that, for...
PURPOSE: To characterize cell-type-specific transcriptional changes during human retinal aging and develop machine learning (ML) model for cellular ag...
The interpretability of GNNs (Graph Neural Network Models) has always been a focal point in the field of compound property prediction. GNNs perform we...
PURPOSE OF REVIEW: Hypertension remains a leading modifiable risk factor for cardiovascular and renal conditions and dementia. Given its rising global...
With the increasing deployment of intelligent robotics in medical rehabilitation and elderly care, sensing modalities and functionalities eventually b...
Early identification of mild cognitive impairment (MCI) progressing to Alzheimer's disease (AD) is of paramount importance. Despite the notable advanc...
BACKGROUND: Mild cognitive impairment (MCI), a precursor to Alzheimer's disease (AD), requires precise early diagnosis. Single-omics approaches often ...
Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by cognitive decline, memory impairment, and impaired daily functio...
End-to-end training in temporal action detection (TAD) has shown great potential for performance improvement by jointly optimizing the video encoder a...
Chronological age is a critical biological trait with substantial relevance in forensic investigations. Growing evidence highlights the role of long n...
Human cognition and behavior rely on the integration of large-scale neural networks that connect the cerebral cortex and subcortical structures. Emerg...
BACKGROUND: Postoperative delirium is associated with increased morbidity, mortality, future cognitive decline, or dementia. Understanding the neural ...
To investigate the role of lipid metabolism abnormalities in the progression of osteoporosis (OP), clarify the impact of the key regulator angiopoieti...
The attrition of telomere length is associated with cellular aging and plays a role in multiple age-related disorders. This study analyzed the relatio...