Latest AI and machine learning research in geriatrics for healthcare professionals.
BACKGROUND: Currently, there is no objective, clinically available tool for the accurate diagnosis of Alzheimer's disease (AD). There is a pressing need for a novel, minimally invasive, cost friendly, and easily accessible tool to diagnose AD, assess disease severity, and prognosticate course. Metabolomics is a promising tool for discovery of new, biologically, and clinically relevant biomarkers f...
BACKGROUND: Language is a valuable source of clinical information in Alzheimer's disease, as it declines concurrently with neurodegeneration. Consequently, speech and language data have been extensively studied in connection with its diagnosis.
BACKGROUND: In recent years, accumulating evidence has linked vitamin D deficiency to cognitive dysfunction and dementia. This study aimed at determin...
BACKGROUND: Deep learning algorithms of cerebral blood flow were used to classify cognitive impairment and frailty in people living with HIV (PLWH). F...
BACKGROUND: With the emergence of competency-based training, the current evaluation scheme of surgical skills is evolving to include newer methods of ...
BACKGROUND: To examine the influence of positive end-expiratory pressure (PEEP) settings on lung mechanics and oxygenation in elderly patients undergo...
BACKGROUND: Aging is a major non-modifiable risk factor for hypertension. Changes in aging are similar to those seen in hypertension in the vasculatur...
BACKGROUND: Due to an aging society, patients with gastric cancer are also getting older. Although total gastrectomy should be avoided for elderly pat...
Atrial fibrillation (AF) is common in the elderly. The treatment of this condition is based on anticoagulation to prevent stroke and systemic arterial...
Rivastigmine is a non-competitive reversible inhibitor of acetylcholinesterase which is approved as one of the fi rst-line treatment options for Alzhe...
In this paper, through the research of digital twin technology, combined with the application of vision sensor, artificial intelligence chip and deep ...
Alzheimer's disease (AD) is a typical neurodegenerative disease, which is clinically manifested as amnesia, loss of language ability and self-care abi...
The purpose of this study was to verify the usefulness of machine learning (ML) for selection of risk factors and development of predictive models for...
The aging of the population is a reality common to the entire Western world, while the time available and human resources are limited. According to ma...
OBJECTIVE: We propose a heartbeat-based end-to-end classification of arrhythmias to improve the classification performance for supraventricular ectopi...
Patient falls, a subcategory of patient safety events, cause further harm and anxiety to patients in healthcare systems. Patient fall reports are a va...
Falls are the leading cause of injuries among older adults, particularly in the more vulnerable home health care (HHC) population. Existing standardiz...
With the vast increase of digital healthcare data, there is an opportunity to mine the data for understanding inherent health patterns. Although machi...
The concern for aging, chronic illness, and dependence is relevant in today's society. The Nursing discipline is responsible for its approach to care....
OBJECTIVE: Geriatric syndromes such as functional disability and lack of social support are often not encoded in electronic health records (EHRs), thu...