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Browse normalized, publication-ready research with direct links to its evidence and source.
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Readable research linked to original sources
Browse normalized, publication-ready research with direct links to its evidence and source.
Loading articles data…
Readable research linked to original sources
Browse normalized, publication-ready research with direct links to its evidence and source.
6 articles
Newest firstBackgroundStandardized evaluation of agentic artificial intelligence (AI) for medication management is lacking. Given the potential lethality of medication errors endorsed or missed by AI, performance evaluation constructs are essential. The purpose of this evaluation was to develop a standardized grading framework for performance evaluation of medication management tasks. MethodsA mixed-methods approach was under…
Open article record in new tab ↗BackgroundElectrolyte replacement is ubiquitous in the acute care setting, but its familiarity cannot belie that even small dosing errors with potassium can cause lethal cardiac arrhythmias. Recently, MedAgentBench offered a benchmark for agentic artificial intelligence (AI) including the ability to correctly dose potassium based on a single rule; however, this does not adequately reflect the clinical complexity o…
Open article record in new tab ↗Large language models (LLMs) increasingly operate in high-stakes settings including healthcare and medicine, where demographic attributes such as race and ethnicity may be explicitly stated or implicitly inferred from text. However, existing studies primarily document outcome-level disparities, offering limited insight into internal mechanisms underlying these effects. We present a mechanistic study of how race an…
Open article record in new tab ↗Electronic Health Records (EHRs) store vast amounts of clinical information that are difficult for healthcare providers to summarize and synthesize relevant details to their practice. To reduce cognitive load on providers, generative AI with Large Language Models have emerged to automatically summarize patient records into clear, actionable insights and offload the cognitive burden for providers. However, LLM summ…
Open article record in new tab ↗While Large Language Models (LLMs) have showcased their potential in diverse language tasks, their application in the healthcare arena needs to ensure the minimization of diagnostic errors and the prevention of patient harm. A Medical Knowledge Graph (KG) houses a wealth of structured medical concept relations sourced from authoritative references, such as UMLS, making it a valuable resource to ground LLMs diagnos…
Open article record in new tab ↗In the evolving landscape of clinical Natural Language Generation (NLG), assessing abstractive text quality remains challenging, as existing methods often overlook generative task complexities. This work aimed to examine the current state of automated evaluation metrics in NLG in healthcare. To have a robust and well-validated baseline with which to examine the alignment of these metrics, we created a comprehensiv…
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