Medicare

Comparison of a Computable Pediatric Sepsis Phenotype Tool in Argentinian and U.S. Cohorts.

OBJECTIVE: Sepsis is a leading cause of mortality in low- and middle-income countries. This study identifies computable pediatric sepsis phenotypes (PedSep A, B, C, and D) previously derived in a U.S. cohort in a new independent Argentine cohort to assess plausibility for its use in personalized clinical trials in Pan-American children. DESIGN: This retrospective cohort study uses data from the Ar...

The Invisible Workforce: An Algorithmic Audit of Nursing, Primary Care, and Holistic Gaps in AI-Generated Survivorship Plans.

OBJECTIVES: Advanced ovarian cancer survivorship requires multidisciplinary coordination. As patients use large language models (LLMs) as clinical navigators, essential professional roles may be inconsistently represented. This study evaluates the comprehensiveness, professional attribution, and readability of LLM-generated survivorship plans. METHODS: An algorithmic audit (N = 50) queried ChatGPT...

AI for Clinical Competency Assessment: Scoping Review of Methods and Applications.

BACKGROUND: Strengthening the global health workforce is central to achieving universal health coverage, but health systems cannot improve what they c...

Clinical DVH metrics as a loss function for 3D dose prediction in head and neck radiotherapy.

PURPOSE: Deep learning-based three-dimensional (3D) dose prediction is widely used in automated radiotherapy workflows. However, most existing models ...

Somalia's lifeline: Digitalization and AI.

Somalia's fragile health system, strained by decades of conflict, climate shocks, and persistently low immunization coverage, remains dangerously vuln...

Robustness Evaluation of Physical versus Virtual Bolus for Breast VMAT Using RegGAN-Based Synthetic CT.

BACKGROUND: Volumetric modulated arc therapy (VMAT) for breast cancer with skin involvement requires a bolus to ensure adequate surface dose. Although...

Development and validation of machine learning models to predict risk of undiagnosed dementia using healthcare claims and electronic health record data.

BackgroundApproximately half of people living with Alzheimer's disease and related dementias are undiagnosed.ObjectiveTo develop and validate algorith...

Clinically interpretable prediction models of stroke functional outcomes: A national cohort study of adults in inpatient rehabilitation facilities in the US.

OBJECTIVE: To predict self-care and mobility function at discharge from inpatient rehabilitation for adults with stroke using only variables from the ...

Biocementation shows a three-dimensional geometry dependence in microfluidic pore networks mapped by deep-learning segmentation.

Microbially induced calcium carbonate precipitation (MICP) can transform granular media into cohesive, load-bearing materials, yet pore-scale design r...

Closing the Health Policy Implementation Gap With Artificial Intelligence.

IMPORTANCE: Health care policies often fail to achieve their goals due to implementation challenges attributable to workforce constraints, fragmented ...

A genome-wide coverage-based pipeline for the identification of host-derived candidate biomarkers in blood cell-free DNA.

We have created a new data-analysis pipeline for the discovery of host-derived candidate biomarkers in blood cell-free DNA sequencing data. Unlike app...

AI-based augmentation of oncology clinical trials.

Oncology clinical trials are often characterized by slow accrual, high failure rates and limited generalizability, reflecting both biological complexi...

A simple parameter to guide plan optimization for robotic pancreas SBRT.

BACKGROUND AND PURPOSE: Pancreatic SBRT planning is challenging due to the proximity of highly sensitive organs at risk. Since automated planning is c...

Online adaptive radiotherapy in pelvic and thoracic cancers - comparing toxicities, clinical outcomes and technical parameters between conventional image-guided radiotherapy and online adaptive radiotherapy - the study protocol for the prospective, registry-based cohort study (PRoART).

BACKGROUND: Conventional image-guided radiotherapy (IGRT) typically relies on a computed tomography (CT)-based treatment planning process (planning CT...

Early Adoption of Autonomous Artificial Intelligence Screening for Diabetic Retinopathy After Introduction of Medicare Billing Code 92229.

PURPOSE: Diabetic retinopathy remains a leading cause of blindness in the United States. Autonomous artificial intelligence (AI) systems for screening...

Evaluating Artificial Intelligence Translation Tools for Language Equivalence of Oncology-Informed Consent Forms From English to Spanish.

PURPOSE: Approximately 8% of the US population speaks primary languages other than English. Limited English proficiency (LEP) contributes to under-rep...

Implementation and Evaluation of an AI-Assisted Telerehabilitation System for Postdischarge Continuation of Rehabilitative Care: Protocol for a Randomized Controlled Trial.

BACKGROUND: The World Health Organization (WHO) launched a Rehabilitation 2030 initiative to call for global action to scale up rehabilitation efforts...

Prediction of Blood Transfusion Need and Dose in Patients With Upper Gastrointestinal Bleeding: Retrospective Multicenter Prediction Model Study.

BACKGROUND: Transfusion thresholds in upper gastrointestinal bleeding are debated; hemoglobin cutoffs of 70-80 g/L are widely cited yet inconsistently...

Evaluation Methods for Inference-Time Retrieval-Augmented and Graph Retrieval-Augmented Large Language Models in Health Care: Scoping Review.

BACKGROUND: Inference-time retrieval augmentation is increasingly used to improve the traceability and verifiability of large language model (LLM) app...

AI-assisted VMAT planning incorporating deep learning-based dose prediction for head and neck cancer: feasibility of quality standardization and human intervention for irregular cases.

BACKGROUND: Volumetric-modulated arc therapy (VMAT) represents a standard of care for head and neck cancer (HNC). However, treatment plan quality depe...