STILWELL, Kan.--(BUSINESS WIRE)--As the time nursing faculty have to supervise students in hands-on procedures continues to decline, many nursing students are not fully developing clinical reasoning ...

The inherent variability and potential inaccuracies of AI-generated output can leave even experienced clinicians uncertain about AI recommendations. This dilemma is not novel; it mirrors the broader ...

Google’s AMIE research AI matched primary care physicians overall in simulated, multi-visit disease-management reasoning and ...

Clinical evaluation of large language models (LLMs) currently relies on static datasets and isolated scenarios that fail to capture the cascading effects of healthcare decisions. We propose the ...

Large language models may not always exhibit poor performance in clinical reasoning and, in specific restricted scenarios, could surpass the capabilities of clinicians, according to a Dec. 11 study ...

AI's integration in medical education presents challenges and opportunities, with findings advocating for curricula that ...

A study comparing the clinical reasoning of an artificial intelligence (AI) model with that of physicians found the AI outperformed residents and attending physicians in simulated cases. The AI had ...

Large Language Models (LLMs) show promise in healthcare tasks but face challenges in complex medical scenarios. We developed a Multi-Agent Conversation (MAC) framework for disease diagnosis, inspired ...

WNMU nursing students navigate complex clinical ethics SILVER CITY, NM — Western New Mexico University nursing students ...

A major study published in Science found that an OpenAI reasoning model outperformed physicians in diagnosing real-world emergency cases, achieving higher accuracy in identifying correct or ...