Latest AI and machine learning research in geriatrics for healthcare professionals.
Time series from different regions of interest (ROI) of default mode network (DMN) from Functional...
State-space models (SSMs) have garnered attention for effectively processing long data sequences, ...
Plasma protein biomarkers have been considered promising tools for diagnosing dementia subtypes due ...
As the aging process accelerates, the incidence of chronic diseases in the elderly is rising. As a r...
Hospital-acquired falls are a continuing clinical concern. The emergence of advanced analytical meth...
Radiologists are tasked with interpreting a large number of images in a daily base, with the respo...
Graph theoretical methods have proven valuable for investigating alterations in both anatomical an...
Epigenetic aging clocks play a pivotal role in estimating an individual's biological age through t...
Six years after the entry into force of the GDPR, European companies and organizations still have ...
Saliency maps have been widely used to interpret deep learning classifiers for Alzheimer's disease...
Biomedical relation extraction is an ongoing challenge within the natural language processing commun...
The vision of IASIS project is to turn the wave of big biomedical data heading our way into action...
Optic deconvolution in light microscopy (LM) refers to recovering the object details from images, ...
BACKGROUND: Recording and coding of ageing syndromes in hospital records is known to be suboptimal. ...
PURPOSE: The purpose of this study was to establish and validate a deep learning model to screen vas...
OBJECTIVE: The global population is aging and the burden of lower urinary tract symptoms (LUTS) is e...
Alzheimer's disease is the most common age-related problem and progresses in different stages, from ...
Patients in the ICU frequently suffer from delirium, which can delay their recovery and may cause si...
Electronic Health Records (EHRs) are a cornerstone of modern healthcare analytics, offering rich dat...
Deep learning models based on convolutional neural networks (CNNs) have been used to classify Alzhei...
Alzheimer's Disease (AD) poses a significant global neurodegenerative challenge, underscoring the ur...