Latest AI and machine learning research in geriatrics for healthcare professionals.
BACKGROUND: Sepsis, frequently complicated by delirium with poor prognosis, is common in the Intensive Care Unit (ICU). Estimated Pulse Wave Velocity (ePWV), a non-invasive arterial stiffness marker, remains unexplored regarding delirium risk in ICU sepsis patients. This study investigated ePWV's association with sepsis-linked delirium and developed a predictive model. METHODS: This retrospective ...
Modern drug discovery joins machine learning with physics-based simulation, but building such a pipeline needs Linux administration, dependency management, format conversion and scripting, which keeps out many of the chemists and biologists who ask the questions. We describe SilicoXplore, a cloud-hosted platform of 31 interoperable modules covering structure preparation, five docking engines, de n...
BACKGROUND: The frailty index (FI) assumes that deficits are interchangeable; the type of individual items matters less than the total count. Machine ...
BACKGROUND: Entering clinical training, dental students must learn to read tooth-centered electronic dental records, but limited teaching time in pati...
Alzheimer's disease (AD) is the most prevalent neurodegenerative disorder worldwide. Conventional downstream interventions targeting β-amyloid (Aβ) an...
ETHNOPHARMACOLOGICAL RELEVANCE: The dried root of Paeonia lactiflora Pall. has a long history of medicinal use in traditional Chinese medicine. Classi...
OBJECTIVE: This study aimed to develop a deep learning model (MST-Net) for the segmentation-free automated and precise differentiation between T2 and ...
Microplastics (MPs) are an emerging pollutant of global concern, creating an urgent need for rapid and accurate monitoring workflows. Deep learning-ba...
Enlarged perivascular spaces (ePVS) are small, sparse MRI-visible markers of cerebral small vessel disease and brain ageing. Their size, low contrast,...
BACKGROUND: Frailty is a significant risk factor for death and disability in older adults with diabetes. Early identification of frailty in this popul...
RATIONALE AND OBJECTIVES: The study aimed to develop and validate a deep learning (DL) model based on X-ray and computed tomography (CT) to diagnose a...
Automated Alzheimer's disease (AD) classification from structural MRI typically employs either feature-engineered machine learning (ML) or end-to-end ...
Cerebrospinal fluid biomarkers, and more recently blood-based biomarkers, are playing a pivotal role in reshaping the clinical management of neurodege...
BACKGROUND: There is increasing recognition that trauma exposure and related psychiatric consequences predict cardiovascular disease risk. However, mo...
BackgroundMild Alzheimer's disease (AD) is associated with alterations in brain activity, which can be detected using electroencephalography (EEG). In...
Postoperative delirium (POD) is a common perioperative complication involving central nervous system dysfunction, particularly among critically ill an...
Accurate dose verification remains a major challenge in particle therapy. Dose monitoring methods such as positron emission tomography (PET) and promp...
Artificial intelligence (AI) has rapidly transformed the potential for opportunistic assessment of bone mineral density (BMD) and bone microarchitectu...
We aimed to systematically analyze the historical evolution of artificial intelligence (AI) in end-stage renal disease (ESRD) management and propose a...
INTRODUCTION: Digital language markers show promise in detecting early cognitive impairment related to Alzheimer's disease (AD), yet their relationshi...