Latest AI and machine learning research in geriatrics for healthcare professionals.
INTRODUCTION: Dementia is a major cause of disability among the elderly, imposing significant financial burdens on healthcare systems. Traditional care approaches contribute to rising costs, especially in high-income countries. Artificial intelligence (AI) offers potential solutions by enhancing various areas of dementia care.
We applied machine learning techniques to build models that predict perceived risks and benefits of using artificial intelligence (AI) algorithms to recruit African American informal caregivers for clinical trials and general health disparity research via social media platforms. In a U.S. sample of 572 family caregivers of a person with Alzheimer's disease and related dementias (ADRD), our applica...
Humanoid robots are increasingly being used in a number of domains. This paper focuses on reviewing the use of the Pepper humanoid robot in healthcare...
Falls pose a significant risk, especially among elderly persons. Recently, radar sensors have been explored for fall detection. In this study, an atte...
Purpose: The primary goal of this study is to explore the application of evaluation metrics to different clustering algorithms using the data provid...
Long-range dependencies are critical for understanding genomic structure and function, yet most conventional methods struggle with them. Widely adop...
Postoperative delirium (POD), a severe neuropsychiatric complication affecting nearly 50% of high-risk surgical patients, is defined as an acute dis...
Objective: Zero-shot methodology promises to cut down on costs of dataset annotation and domain expertise needed to make use of NLP. Generative larg...
The population of older adults is steadily increasing, with a strong preference for aging-in-place rather than moving to care facilities. Consequent...
Alzheimer's disease (AD) leads to progressive cognitive decline, making early detection crucial for effective intervention. While deep learning mode...
We propose an end-to-end trainable, cross-category method for reconstructing multiple man-made articulated objects from a single RGBD image, focusin...
Large language models (LLMs) have emerged as powerful tools for medical information retrieval, yet their accuracy and depth remain limited in specia...
Accurate and real-time three-dimensional (3D) pose estimation is challenging in resource-constrained and dynamic environments owing to its high comp...
Image retargeting aims to change the aspect-ratio of an image while maintaining its content and structure with less visual artifacts. Existing metho...
Human activity recognition is increasingly vital for supporting independent living, particularly for the elderly and those in need of assistance. Do...
Background: Artificial Intelligence (AI) clinical decision support (CDS) systems have the potential to augment surgical risk assessments, but succes...
Traditional hospital-based medical examination methods face unprecedented challenges due to the aging global population. The Internet of Medical Thi...
Efficiently understanding long-form videos remains a significant challenge in computer vision. In this work, we revisit temporal search paradigms fo...
Previous research has established type 2 diabetes mellitus as a significant risk factor for various disorders, adversely impacting human health. While...
Objective: Traditional phone-based surveys are among the most accessible and widely used methods to collect biomedical and healthcare data, however,...