Geriatrics

Clinical implementation of AI for vertebral fracture detection in CT aligned with fracture liaison services: high prevalence of undiagnosed vertebral fractures.

UNLABELLED: We assessed feasibility and effectiveness of AI-based VF screening in CT, integrated with a local FLS. The system identified VFs in 14% of patients, half previously unrecognized or untreated. This suggests that 2-3 patients with VFs were identified daily at our hospital, highlighting the potential clinical impact of AI-assisted detection. PURPOSE: To evaluate the feasibility and effica...

Bridging Population Patterns and Individual Prediction: Framework for Prospective Multimorbidity Study.

BACKGROUND: Multimorbidity has become a major global public health challenge. However, existing research primarily emphasizes the identification of disease patterns at the population level and lacks the capacity to provide predictive insights into individual future pattern membership. Bridging this gap is crucial for personalized prevention and management. OBJECTIVE: This study aims to propose an ...

Clinical and pathologic correlations of machine learning quantification of Aβ deposits across 3 brain regions of decedents with Alzheimer disease.

Machine learning enables scalable quantification of neuropathology, offering deeper phenotyping of Alzheimer's disease (AD). In this validation study,...

Quantitative AI Volumetry Profiling Regional Muscle Hypotrophy in Chronic Limb-Threatening Ischemia.

BACKGROUND: Chronic limb-threatening ischemia (CLTI) leads to severe functional impairment and degeneration of lower-limb musculature. Although muscle...

Personalised health plan development using agentic AI in Singapore's national preventive care programme: a pilot study.

The workforce shortages caused by aging populations demand a transition from reactive to preventive healthcare strategies. Generative Artificial Intel...

EENet-RLA: An Explainable Prediction Learning Framework for Alzheimer's Disease Classification from EEG Signals.

Alzheimer's disease (AD) is a prevalent neurodegenerative disorder affecting millions worldwide. Electroencephalography (EEG), a non-invasive, cost-ef...

Usability of a deep learning platform for detecting radiographic bone loss and furcation involvement.

BACKGROUND: Assessing radiographic bone condition is important for periodontal diagnosis. The accuracy of radiographic interpretation depends highly o...

GenX-associated molecular signatures overlap with testicular aging and male infertility: a multi-omics integration analysis.

GenX (HFPO-DA), a short-chain per- and polyfluoroalkyl substance (PFAS) substitute, is implicated in testicular toxicity. GenX-related genes were inte...

A machine learning model to detect falls mimicking cardiac arrest-related collapse based on wrist-derived accelerometry: the DETECT-2 study.

AIMS: In wearable-based automated cardiac arrest detection technology, photoplethysmography (PPG) is the most commonly used sensor to detect the absen...

Resource-stratified machine learning framework for cognitive status classification and mild cognitive impairment to dementia progression prediction.

Artificial intelligence-based biomarkers for the diagnosis and treatment of neurological conditions: a narrative review.

Artificial intelligence (AI) is transforming biomarker discovery in neurology by overcoming key limitations of conventional approaches that are often ...

Association of stress hyperglycemia ratio with the incidence of delirium in critically ill patients: a retrospective cohort study with exploratory machine-learning analyses.

Preoperative Risk Score for Mortality Within 3 Years of Elective Aortobifemoral Artery Bypass.

BACKGROUND: The purpose of this study was to create a risk score for mortality within 3 years of elective aortobifemoral artery bypass for aortoiliac ...

Modeling inter-slice dependencies with temporal graph learning for Alzheimer's disease.

Accurate and early diagnosis of Alzheimer's disease (AD) remains a major clinical challenge, particularly in distinguishing mild cognitive impairment ...

Evaluation of kidney biological age based on IgG N-glycosylation profiles and its association with chronic kidney disease in the context of predictive, preventive and personalized medicine.

BACKGROUND: Chronic kidney disease (CKD) is associated with premature aging, which reflects in the difference between biological age and chronological...

Machine learning prediction model for delirium after heart valve replacement with cardiopulmonary bypass: A large-scale cohort study.

OBJECTIVE: Postoperative delirium (POD) is a common and severe complication following heart valve replacement (HVR) with cardiopulmonary bypass (CPB),...

Machine Learning-Integrated Pharmacophore, DFT Analysis, and molecular dynamics of Diosmetin as a potent ache inhibitor with neuroprotective activity in a Scopolamine-Induced alzheimer's zebrafish model.

Alzheimer's Disease (AD) is a degenerative disorder of the brain that causes a gradual loss of cognitive function. The cholinergic hypothesis suggests...

Exploring feature importance in machine learning for neuroimaging traits in Alzheimer's disease across a multiethnic cohort.

BackgroundAlzheimer's disease (AD) affects 55 million people worldwide, projected to reach 139 million by 2050; yet, most machine learning (ML)-based ...

Inferring preoperative cognitive function from intraoperative electroencephalography in elderly patients using machine learning.

To develop and evaluate machine learning (ML) models that infer preoperative cognitive function from intraoperative electroencephalography (EEG). This...

AI-Driven Mental Health Support for Caregivers of Individuals With Alzheimer Disease: Systematic Literature Review and Development of a Conceptual Framework.

BACKGROUND: Caregivers supporting individuals with Alzheimer disease and related dementias (AD/ADRD) frequently encounter prolonged emotional strain, ...