Latest AI and machine learning research in geriatrics for healthcare professionals.
INTRODUCTION: Artificial intelligence (AI) models have been applied to differential dementia detection tasks in brain images from curated, high-quality benchmark databases, but not real-world data in hospitals.
6D pose estimation of rigid objects is a long-standing and challenging task in computer vision. Recently, the emergence of deep learning reveals the potential of Convolutional Neural Networks (CNNs) to predict reliable 6D poses. Given that direct pose regression networks currently exhibit suboptimal performance, most methods still resort to traditional techniques to varying degrees. For example, t...
To development a deep learning（DL） model based on conventional MRI for automatic segmentation and differential diagnosis of nasopharyngeal carcinoma（N...
Predicting fall risk in the elderly is crucial for enhancing safety and well-being. Aging and chronic diseases often impair balance, increasing fall r...
IMPORTANCE: Recent data point to the impact of non-traditional environmental and social factors on Alzheimer's Disease-Related Dementias (ADRD) mortal...
Cellular senescence is a complex biological process with a dual role in tissue homeostasis and aging-related pathologies. Accumulation of senescent ce...
As the older adult population continues to expand, the demands on the healthcare system intensifies, necessitating the development of technologies tha...
Deep Learning in Image Registration (DLIR) methods have been tremendously successful in image registration due to their speed and ability to incorpora...
Alzheimer's disease (AD) is a neurodegenerative disorder characterized by a progressive cognitive decline, necessitating early diagnosis for effective...
The exploration-exploitation dilemma is one of the fundamental challenges in deep reinforcement learning (RL). Agents must strike a trade-off between ...
BACKGROUND: Hip fractures are associated with reduced mobility, and higher morbidity, mortality, and healthcare costs. Approximately 90% of hip fractu...
OBJECTIVE: To compare the performance of machine learning and logistic regression algorithms in predicting emergence delirium (ED) in elderly patients...
BACKGROUND: Diabetes mellitus has been shown to increase the risk of dementia, with diabetic patients demonstrating twice the dementia incidence rate ...
BACKGROUND: Frailty, a significant predictor of adverse health outcomes, has become a focal point of research, particularly with the advent of artific...
BACKGROUND: Monitoring intrinsic capacity and implementing appropriate interventions can support healthy aging. There are, though, few tools available...
OBJECTIVE: Identifying cognitive impairment early enough could support timely intervention of cognitive impairment and facilitate successful cognitive...
While personalization has been explored in traditional autonomous driving systems, it remains largely overlooked in end-to-end autonomous driving (E...
Benefiting from the advances in large language models and cross-modal alignment, existing multimodal large language models have achieved prominent p...
Reasoning plays a crucial role in advancing Multimodal Large Language Models (MLLMs) toward Artificial General Intelligence. However, existing MLLM ...
Fast diagnosis and repair of enterprise network failures is critically important since disruptions cause major business impacts. Prior works focused...