Geriatrics

Spatial amyloid-informed multimodal brain age as an early marker of Alzheimer's-related vulnerability and risk stratification.

BACKGROUND: Brain age gap (BAG)-the difference between predicted and chronological age-captures neurobiological aging, but MRI-only models insufficiently reflect Alzheimer's disease (AD) pathology. Whether incorporating regional amyloid-β (Aβ) positron emission tomography (PET) improves sensitivity to early AD processes remains unknown. OBJECTIVES: To develop an amyloid-informed multimodal BAG mod...

Opportunistic osteoporosis screening using CT-based Hounsfield units: a machine learning approach for preoperative spine surgery planning.

Perceived Potential and Challenges of Supporting Coronary Artery Disease Treatment Decisions With AI: Qualitative Study.

BACKGROUND: Coronary revascularization decision-making for patients with coronary artery disease (CAD) can be complex and challenging. Artificial inte...

OpenMetabolics: estimating energy expenditure using a smartphone worn in a pocket.

Physical inactivity is the fourth largest cause of global mortality. Health organizations have requested a tool to objectively measure physical activi...

Identifying sex-specific predictors of frailty in Korean community-dwelling older adults using interpretable machine learning.

Salivary extracellular vesicles and Raman spectroscopy in precision diagnostics of type 2 diabetes.

Type 2 Diabetes (T2D) remains a major global health issue, driven by sedentary lifestyles and aging populations, emphasizing the urgent need for preci...

Open-Source Machine Learning Computed Tomography Scan Segmentation for Spine Osteoporosis Diagnostics.

BACKGROUND AND OBJECTIVES: Dual-energy x-ray absorptiometry (DXA) is the standard for assessing bone mineral density (BMD); however, its accuracy is l...

Effectiveness of Informed AI Use on Clinical Competence of General Practitioners and Internists: Pre-Post Intervention Study.

BACKGROUND: Artificial intelligence (AI) shows promise in clinical diagnosis, treatment support, and health care efficiency. However, its adoption in ...

Hybrid neural-cognitive models reveal how memory shapes human reward learning.

A long-standing challenge for psychology and neuroscience is to understand the transformations by which past experiences shape future behaviour. Rewar...

Explainable machine learning-based 28-day mortality prediction model for elderly patients with acute kidney injury.

Elderly patients with acute kidney injury (AKI) face a significantly increased mortality risk. Recent advances in machine learning technology have mad...

Comparative analysis of supervised and ensemble models with unsupervised exploration for alzheimer's disease prediction.

Alzheimer's disease is a progressive neurodegenerative disorder characterized by memory loss and cognitive decline, with no known cure. Early detectio...

Large-scale proteomic profiling identifies distinct inflammatory phenotypes in acute respiratory distress syndrome: a multicentre, prospective cohort study.

BACKGROUND: Host responses during acute respiratory distress syndrome are highly heterogeneous, contributing to inconsistent therapeutic outcomes. Pro...

Factors and determinants of primary care to tertiary care referrals in Singapore: A multi-centre analysis using artificial intelligence-powered large language models.

BACKGROUND: As Singapore adopts a population health approach under Healthier Singapore (Healthier SG), optimizing healthcare resources is crucial. We ...

Biological aging across the metabolic dysfunction-associated steatotic liver disease spectrum: A systematic review.

BACKGROUND AND AIMS: Metabolic dysfunction-associated steatotic liver disease (MASLD) is a growing global health burden. Geroscience posits that accel...

Association of urinary heavy metals with osteoporosis in US adults using interpretable machine learning.

BACKGROUND: Exposure to heavy metals in the environment has always been the focus of public concern. More and more evidence suggests that heavy metal ...

Interpretable Machine Learning Model Using Digitized US Features for Classifying Complex Thyroid Nodules.

Purpose To develop a digitized integrated feature-based interpretable machine learning classification model to accurately recognize complex thyroid no...

Using Smartphone-Based Digital Phenotyping to Predict Relapse in Serious Mental Disorders Among Slum Residents in Dhaka, Bangladesh: Protocol for a Machine Learning Study.

BACKGROUND: Serious mental illnesses (SMIs) are associated with high relapse rates and limited access to continuous care, particularly in low-resource...

Association of lactate-to-albumin ratio with 28-day mortality in elderly sepsis patients: a retrospective MIMIC-IV database analysis.

BACKGROUND: The lactate-to-albumin ratio (LAR) is correlated with mortality in critically ill patients; however, its predictive value for sepsis in th...

PRDX6 as a Ferroptosis-Related Hub Gene in the Entorhinal Cortex of Alzheimer's Disease: A Multidimensional Bioinformatics and Experimental Validation Study.

Ferroptosis, an iron-dependent regulated cell death form, is a key pathogenic mechanism in Alzheimer's disease (AD), especially in the entorhinal cort...

Gender-related facilitators and barriers to participation in research on aging using fuzzy cognitive mapping.

In the context of cognitive neuroscience research on aging, older women are often overrepresented in observational research, whereas men are overrepre...