Latest AI and machine learning research in health policy for healthcare professionals.
Early identification and referral of inflammatory breast cancer (IBC) remains challenging within large healthcare systems, limiting access to specialized care. We developed and evaluated an artificial intelligence-driven platform integrating natural language processing (NLP) with electronic health records to systematically identify potential IBC cases across five campuses. Our platform analyzed 8,...
Marked variability in inpatient hospitalization costs poses significant challenges to healthcare quality, resource allocation, and patient outcomes. Traditional methods like Diagnosis-Related Groups (DRGs) aid in cost management but lack practical solutions for enhancing hospital care value. We introduce a novel methodology for outlier detection in Electronic Health Records (EHRs) using Conformal ...
SIGNIFICANCE: Functional magnetic resonance imaging provides high spatial resolution but is limited by cost, infrastructure, and the constraints of an...
Technical debt prediction (TDP) is crucial for the long-term maintainability of software. In the literature, many machine-learning based TDP models ha...
Therapeutic clinical trial enrollment does not match glioma incidence across demographics. Traditional statistical methods have identified independent...
Breast self-examination is a very cost-reducing approach that significantly decreases the cost burdens associated with medical equipment, fees of heal...
BACKGROUND: Familial hypercholesterolemia (FH) is a genetic condition which elevates cholesterol levels and increases risk of premature cardiac events...
Persistent geographic and specialty-based disparities in health care workforce distribution have created critical gaps in rural health care access, re...
In 1989, the World Wide Web was proposed as a practical solution to connect scientists globally. That innovation later transformed how knowledge was a...
Artificial intelligence (AI) and digital health (DH) solutions are reshaping musculoskeletal (MSK) care across diagnostics, treatment planning, workfl...
: Adverse pregnancy outcomes (APOs), which include hypertensive disorders of pregnancy (gestational hypertension, preeclampsia, and related disorders)...
Lung cancer remains a leading cause of global cancer mortality, demanding precise diagnostic tools for accurate subtype classification. This paper int...
This review focuses on integrating artificial intelligence (AI) into healthcare, particularly for predicting adverse events, which holds potential in ...
Floods lead to adverse impacts not only in financial terms but also on the health of the exposed population. We report on health-related Quality of Li...
The emergence of digital technology has led to a significant increase in the importance of educational credential storage, exchange, and verification ...
Emerging pharmaceutical markets like Brazil, India, and China have seen significant growth due to rising medication demand, expanding middle-class acc...
This study compared machine-learning models for predicting recurrence-free survival (RFS), disease-specific survival (DSS), and overall survival (OS) ...
The rapid integration of artificial intelligence (AI) into healthcare has raised many concerns about race bias in AI models. Yet, overlooked in this d...
Satellite data have long been recognized as valuable for air quality applications. These applications are in a stage of rapid growth: new geostationar...
Artificial intelligence (AI) presents new opportunities to advance value-based healthcare in orthopedic surgery through 3 potential mechanisms: agency...