Latest AI and machine learning research in geriatrics for healthcare professionals.
This study examines the potential causal relationship between head injury and the risk of developing Alzheimer's disease (AD) using Bayesian networks and regression models. Using a dataset of 2,149 patients, we analyze key medical history variables, including head injury history, memory complaints, cardiovascular disease, and diabetes. Logistic regression results suggest an odds ratio of 0.88 fo...
Accurately locating key moments within long videos is crucial for solving long video understanding (LVU) tasks. However, existing benchmarks are either severely limited in terms of video length and task diversity, or they focus solely on the end-to-end LVU performance, making them inappropriate for evaluating whether key moments can be accurately accessed. To address this challenge, we propose M...
The efficient processing of long context poses a serious challenge for large language models (LLMs). Recently, retrieval-augmented generation (RAG) ...
Mental health remains a critical global challenge, with increasing demand for accessible, effective interventions. Large language models (LLMs) offe...
Long-context modeling is crucial for next-generation language models, yet the high computational cost of standard attention mechanisms poses signifi...
This study presents the development and testing of a conversational speech system designed for robots to detect speech biomarkers indicative of cogn...
Access to health resources is a critical determinant of public well-being and societal resilience, particularly during public health crises when dem...
The Internet of Things (IoT) revolutionizes smart city domains such as healthcare, transportation, industry, and education. The Internet of Medical ...
The early diagnosis of Alzheimer's Disease (AD) through non invasive methods remains a significant healthcare challenge. We present NeuroXVocal, a n...
In the analysis of remote healthcare monitoring data, time series representation learning offers substantial value in uncovering deeper patterns of ...
Identifying cognitive impairment within electronic health records (EHRs) is crucial not only for timely diagnoses but also for facilitating research...
The differential diagnosis of neurodegenerative diseases, characterized by overlapping symptoms, may be challenging. Brain imaging coupled with arti...
Existing models typically segment either the entire 3D frame or 2D slices independently to derive clinical functional metrics from ventricular segme...
In remote healthcare monitoring, time series representation learning reveals critical patient behavior patterns from high-frequency data. This study...
There are many approaches in mobile data ecosystem that inspect network traffic generated by applications running on user's device to detect persona...
To create usable and deployable Artificial Intelligence (AI) systems, there requires a level of assurance in performance under many different condit...
The Kondinin region in Western Australia faces significant agricultural challenges due to pervasive weed infestations, causing economic losses and e...
Molecular communication (MC) provides a foundational framework for information transmission in the Internet of Bio-Nano Things (IoBNT), where effici...
Medical image segmentation remains a formidable challenge due to the label scarcity. Pre-training Vision Transformer (ViT) through masked image mode...
Cerebral perfusion plays a crucial role in maintaining brain function and is tightly coupled with neuronal activity. While previous studies have exa...