Latest AI and machine learning research in health policy for healthcare professionals.
OBJECTIVE: To develop a machine learning (ML) algorithm that improves accuracy compared to the Hierarchical Condition Category (HCC) score used by the Centers for Medicare and Medicaid Services to risk-adjust payments for > 65 million Americans. STUDY DESIGN AND SETTING: Prognostic study using Medicare claims data to train "Franklin", an ML algorithm predicting one-year costs, trained using identi...
OBJECTIVE: To examine whether the economic benefits of bariatric surgery differ by patient subgroups, with the aim of identifying those that may yield the most favorable cost profile for improved return on investment in an exploratory analysis. STUDY SETTING AND DESIGN: To identify patient subgroups via the "mTree" (matching + decision tree) method, we conducted analyses of total expenditures 3 ye...
Only when scientific evidence moves beyond research conclusions and is translated into clinical decision-making, organizational systems, and standard ...
Under the framework of evidence-based practice (EBP), evidence-based knowledge is integrated systematically into clinical care and continuously update...
The game changers in mental health and substance use disorder treatment have been shaped by historical sea changes marked by transformative advancemen...
Consumers increasingly turn to artificial intelligence (AI) systems, including search engines and large language models (LLMs), for immediate food saf...
BACKGROUND: Current literature on AAA is characterized by selective outcome reporting, while guideline recommendations are frequently based on studies...
SIGNIFICANCE: Low-cost optoacoustic imaging based on light-emitting diodes (LEDs) offers an affordable alternative to traditional laser-based systems,...
Medical applications of mathematical modeling, including machine learning models, knowledge graphs, and health digital twins, primarily involve the pr...
BACKGROUND: Anecdotal evidence suggests that an increasing number of people are turning to generative artificial intelligence (GenAI) tools or artific...
Stroke remains a leading cause of death and disability worldwide. In response, many governments have developed stroke policies emphasizing prevention,...
BACKGROUND: Generative artificial intelligence (AI) tools, such as ChatGPT, are increasingly used in higher education and have raised significant conc...
Wound care is an increasing global challenge, with older adults among those most affected. As populations age, the demand for effective and efficient ...
Picture Archiving and Communication Systems (PACS) have evolved over decades in response to changes in imaging technology, network and data storage in...
The application of reinforcement learning (RL) in real-world scenarios is limited due to safety concerns and the distribution-shift challenge in the o...
BACKGROUND: Heart failure (HF) hospitalization readmissions are associated with a high mortality rate and strain the health care system. Both clinical...
Managing risks from water pollution is central to public health, environmental quality, and economic prosperity worldwide. While improvements in water...
Psychological treatments are increasingly being developed and delivered using platforms such as mobile applications, online modules, virtual reality, ...
Total phosphorus (TP) poses a severe threat to the health of fluvial and lacustrine ecosystems in China. Accurate prediction of TP and analysis of its...
Accurate plant health monitoring relies on hyperspectral imagery to extract vegetation spectral signatures and compute vegetation indices (VIs), which...