Medicare

Patient and Facility Factors Associated with Uptake of NTAP-Billed AI to Identify Suspected LVO in Ischemic Stroke.

PURPOSE: Medicare's New Technology Add-On Payment (NTAP) incentivizes the adoption of innovative technologies. We examined factors associated with the use of NTAP-billed artificial intelligence (AI) software for detecting large vessel occlusion (LVO) in acute ischemic stroke (AIS) patients requiring thrombolytic treatment. METHODS: Using nationally representative Medicare 5% Research Identifiable ...

Outer nuclear layer thinning as an in vivo biomarker for discriminating probable FTLD-tau from probable FTLD-TDP with PET-supported subtyping.

BACKGROUND AND OBJECTIVES: Outer nuclear layer (ONL) thinning has been identified in frontotemporal lobar degeneration (FTLD); however, its utility for distinguishing the subtypes of FTLD-tauopathy (FTLD-tau) and TDP-43 proteinopathy (FTLD-TDP) remains unknown. We investigated whether ONL thickness provides a subtype-informative retinal signal for differentiating PET-supported probable FTLD-tau (p...

Scalable nonlinear Cox modeling via random Fourier features with analytic uncertainty.

BACKGROUND: The Cox proportional hazards model often fails to capture complex biomedical risk structures, such as U-shaped biomarker associations, due...

Comparative 10-year performance of mammography artificial intelligence, polygenic, and clinical breast cancer risk models in the Kaiser Permanente Research Bank.

BACKGROUND: We compared performance across 3 breast cancer risk domains-clinical, polygenic, and mammography artificial intelligence-alone and in comb...

Increasing the Reliability of Functional Connectivity by Predicting Long-Scan Functional Connectivity based on Short-Scan Functional Connectivity: Model Exploration, Explanation, Validation, and Application.

Functional connectivity (FC) is a widely used metric in functional magnetic resonance imaging (fMRI) research. However, its reliability has long been ...

Electronics with switchable flexibility for 3D conforming neural interfaces.

The intricate cortical folds of large primates physically restrict access to substantial portions of neural information via interface devices. Here, w...

Dynamic Memory-Enhanced Recurrent Neural Networks with Temporal Attention for Robust Long-Range Connectivity Inference.

Accurate estimation of long-range directed connectivity remains a critical challenge in recurrent neural network design due to vanishing gradients ove...

GnnDebugger: GNN based error correction in De Bruijn Graphs.

BACKGROUND: Modern sequencing technologies have enabled the reconstruction of complete mammalian genomes from telomere to telomere. However, scaling t...

Feasibility and psychometric evaluation of large language model-generated radiology learning materials for board examination preparation: a prospective pilot study.

BACKGROUND: Large language models (LLMs) can generate structured educational content at scale, yet their role in postgraduate radiology training remai...

Structural Evolution of Pt Nanoclusters Driven by CO Reactant Pressure and Catalyst Temperature.

The atomic-scale structure of a metal catalyst surface controls its catalytic performance. Through a combination of high-pressure scanning tunneling m...

Knowledge-Augmented Large Language Model for Multimodal Electronic Health Record-Based Risk Prediction: Development and Validation Study.

BACKGROUND: Accurate clinical outcome prediction using electronic health records (EHRs) is crucial for patient care and resource allocation. EHRs incl...

Stage-transition mechanism of forest-grass vegetation coverage in machine-learning simulation of event-scale suspended sediment concentration processes.

Vegetation restoration is widely regarded as a key measure for mitigating soil erosion in the middle reaches of the Yellow River. However, the regulat...

A Structured Comparison of the Coalition for Health AI Responsible AI Guide and South Korea's Trustworthy AI Guideline for Health Care AI Assurance: Comparative Framework Analysis.

BACKGROUND: Trustworthy artificial intelligence (AI) in health care requires assurance frameworks that translate ethical principles into measurable go...

AI-Enhanced Point-of-Care Diagnostics for Infectious Diseases in Resource-Limited Settings: A Scoping Review.

OBJECTIVES: To systematically map the extent and nature of research on AI-enhanced point-of-care (POC) and rapid diagnostic technologies for infectiou...

Toward Effective Graph Long-Tailed Learning With Noisy Labels.

Graph long-tailed learning has garnered significant research attention. However, prevailing works in this domain typically assume the cleanliness of t...

Pancreatic Cancer Risk Stratification Across Diabetes Stages: Development and Internal Validation of a Machine Learning Model.

BACKGROUND: Pancreatic cancer is diagnosed at advanced stages in diabetes patients. Existing prediction models require complete historical data and fo...

Impact of middle meningeal artery embolization on neurological complications and discharge outcomes in chronic subdural hematoma: A machine learning-based comparative study.

INTRODUCTION: Chronic subdural hematoma (cSDH) predominantly affects older adults, often those with prior head trauma, anticoagulation therapy, or chr...

Review Topic: Don't Cancer Doctors Offer Good-Quality Care?

We offer the perspectives of two veterans on the last quarter century of quality improvement efforts in oncology care. We believe that our colleagues ...

Smartwatch-derived exercise metrics as predictors of early hypertension: a prospective observational study.

BACKGROUND: Early identification of individuals at risk for hypertension is essential for effective cardiovascular disease. Physiological and activity...

Development and validation of a machine learning-based prediction model for malnutrition risk in peritoneal dialysis patients: a multi‑center retrospective study.

PURPOSE: To develop and validate a machine learning (ML)‑based model for predicting malnutrition risk in patients undergoing maintenance peritoneal di...