Latest AI and machine learning research in us health policy for healthcare professionals.
The fragility index continues to be promoted as a measure of trial robustness despite evidence that it is little more than statistical significance in a different form. Two misconceptions have been particularly persistent throughout the fragility literature: first, that the fragility index can be directly compared with patients lost to follow-up, and second, that fragility metrics provide unique i...
BACKGROUND: The rapid uptake of generative artificial intelligence (GenAI) in higher education has increased both enthusiasm and concern. While students' use of GenAI has been widely discussed, empirical research focusing on nurse educators' own experiences and perceptions remains limited. This systematic review synthesizes evidence on nurse educators' experiences of using generative artificial in...
POURPOSE: To provide an update on the role of multiparametric magnetic resonance imaging (mpMRI) in active surveillance (AS) of prostate cancer, with ...
BACKGROUND: Biomedical informatics plays a central role in supporting learning health systems (LHSs) which aim to continuously improve care by transfo...
BACKGROUND: Current risk scores for sudden cardiac death (SCD) in hypertrophic cardiomyopathy (HCM) have limited ability to identify high-risk subgrou...
OBJECTIVE: To predict self-care and mobility function at discharge from inpatient rehabilitation for adults with stroke using only variables from the ...
BACKGROUND: Frequent transthoracic echocardiograms (TTEs) are required to monitor for left ventricular systolic dysfunction (LVSD) in patients with ob...
PURPOSE: This review explores how e-health interventions are utilized within neonatal intensive care units to support nursing practice, with particula...
IMPORTANCE: Health care policies often fail to achieve their goals due to implementation challenges attributable to workforce constraints, fragmented ...
INTRODUCTION: Oral capsules for gastric submucosal delivery represent a fundamentally new route of administration for biologics, which are currently l...
Artificial intelligence (AI) is playing an increasingly central role in drug discovery and the pharmaceutical industry more broadly. However, despite ...
BACKGROUND: The medical black bag is synonymous with physicians, especially general practitioners, who are expected to be ready to provide care across...
BACKGROUND: Pseudomonas aeruginosa is a highly resistant pathogenic bacterium known for causing infections,particularly in immunocompromised patients....
PURPOSE: Diabetic retinopathy remains a leading cause of blindness in the United States. Autonomous artificial intelligence (AI) systems for screening...
BACKGROUND: Occlusion myocardial infarction (OMI) is increasingly recognized among NSTEMI patients, yet current diagnostic paradigms may fail to detec...
PURPOSE: Machine learning (ML) has transformed oncological risk prediction by enabling personalized therapeutic strategies. Local tumor control remain...
Purpose To evaluate whether the artificial intelligence (AI)-quantified mean thoracic skeletal muscle (TSM) attenuation from coronary artery calcium (...
INTRODUCTION: Improving the efficiency and accuracy of annotation and extraction of performance data from mouse behavioral tasks will improve both the...
BACKGROUND: Age-related structural and functional remodeling of the heart and vessels increases cardiovascular disease (CVD) risk, yet comprehensive a...
Aim: We aimed to compare Quan and colleagues (2011) established weights for the Charlson Comorbidity Index (CCI) conditions to autism-specific weights...