Geriatrics

End-to-end molecular structure elucidation from multimodal NMR spectra images using vision transformers.

Nuclear magnetic resonance (NMR) spectroscopy is a cornerstone technique for molecular structure elucidation, but interpreting complex NMR spectra remains challenging and often relies on expert-driven, heuristic workflows. Recent deep learning approaches have enabled spectrum-to-structure prediction, yet many depend on peak-level text annotations that discard informative intensity patterns and are...

Multi-dimensional risk prediction and genetic architecture of aspiration pneumonia: a population-based analysis.

BACKGROUND: Aspiration pneumonia represents a significant but understudied cause of morbidity and mortality, particularly among aging populations with neurological comorbidities. Current risk stratification tools rely on single-dimensional clinical data, limiting their predictive accuracy and population health utility. This study aimed to develop comprehensive risk prediction models and identify g...

When Trees Guide Molecules: Multiobjective Search in de Novo Drug Design.

Seen as a problem of guided exploration with multiple objectives, molecular design requires carefully elaborated decision-tree-based strategies for tr...

Epigenetic-Metabolic interplay in chronic kidney disease mortality: insights from grimage acceleration and transcriptomic profiling.

BACKGROUND: Chronic kidney disease (CKD) is associated with a substantially elevated risk of mortality. Although GrimAge acceleration (GAA) and metabo...

Gray matter brain age predicts cognitive outcome one year after ischemic stroke.

BackgroundPredicting post-stroke cognitive impairment (PSCI) remains challenging.ObjectiveThis study validated two brain age metrics-Gray Matter Brain...

Machine learning-driven high-throughput screening of electrocatalysts and electrolytes for electrochemical surfaces and interfaces.

Machine learning (ML) establishes a new paradigm for electrocatalyst and electrolyte research by coupling high-throughput screening (HTS) with a data-...

Endoscopy-based Deep Learning Algorithms versus Endoscopists in Early Esophageal Squamous Cell Carcinoma Detection: A Systematic Review and Meta-Analysis.

INTRODUCTION: To compare the diagnostic performance of endoscopy-based deep learning (DL) algorithms with endoscopists of different experience levels ...

A Voyage on Computer Aided Intelligent Algorithms for the Segmentation of Brain Tissues for Neurodisorder Diagnosis.

Neurodisorders pose a considerable burden to global health, frequently requiring early treatment and diagnosis to avoid irreversible cognitive and mot...

Explainability in context: calibrating appropriate trust and reliance in artificial intelligence.

BACKGROUND AND SIGNIFICANCE: Predictive artificial intelligence (AI) promises to transform care delivery, enhance patient safety, and improve health o...

Diagnostic Performance of General Practitioners in Carotid Plaque Detection Using AI-Enhanced Point-of-Care Ultrasound After Systematic Training.

PURPOSE: While point-of-care ultrasound (POCUS) has been integrated into daily practice by general practitioners (GPs) in some countries, there is a p...

Integrated transcriptomic analysis identifies liver aging-driven fibrosis signatures and reveals therapeutic strategies based on medicine-food homology.

Despite its strong regenerative capacity, liver aging paradoxically increases susceptibility to fibrosis and metabolic dysfunction-associated steatoti...

OCT-based optic neuropathy diagnosis using explainable and privacy-preserving machine learning.

Glaucoma shares similarities with neurodegenerative conditions like dementia, Parkinson's disease, and ischaemic optic neuropathy, which affect ocular...

Research on a long-haul transmission-line distributed vibration signal denoising method based on dual-fiber sensing and weakly supervised learning.

Long-haul distributed fiber-optic vibration monitoring for overhead transmission lines enables continuous sensing along the entire corridor. However, ...

Comment on "integrating machine learning into fracture liaison services: Toward precision risk stratification in osteoporosis care".

The eye sees what the mind knows: Eye tracking and artificial intelligence to assess surgical resident level of expertise.

BACKGROUND: Surgical education continues to strive to move beyond traditional time-based competency metrics. As gaze behaviors can reflect underlying ...

Fusing Structural Phenotypes with Functional Data for Early Prediction of Primary Angle-Closure Glaucoma Progression.

PURPOSE: To classify eyes as slow or fast glaucoma progressors in patients with primary angle-closure glaucoma (PACG) using an integrated approach com...

Targeting Tau-Mitochondrial Crosstalk in Alzheimer's Disease: Integrative Multi-Omics and Artificial Intelligence-Driven Tools for the Development of Disease-Modifying Therapeutics.

Alzheimer's disease (AD) is a progressive neurodegenerative illness marked by cognitive impairment, synaptic dysfunction and neuronal death. Tau prote...

TVRN: Invertible Neural Networks for Compression-Aware Temporal Video Rescaling.

To fit diverse display and bandwidth constraints, high-frame-rate videos are temporally downscaled to low-frame-rate (LFR) and later upscaled, requiri...

Proactive soft-failure prediction in optical transport networks via physics-inspired features and Infrastructure-as-Code orchestration.

Optical transport networks rely on reactive fault management, which guarantees service disruption during the onset of soft failures. We present a fram...

Mapping AI regulation in health care with the Health & AI Policy Index.

Artificial intelligence (AI) policy for health care is expanding in a fragmented landscape. In a January 1, 2026 snapshot of the Health & AI Policy In...