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Atropos Health’s Arjun Mukerji, PhD, Explains RWESummary: A Framework and Test for Choosing LLMs to Summarize Real-World Evidence (RWE) Studies
Large language models are increasingly used to turn complex study output into plain-English summaries. But how do we know which models are safest and most reliable for healthcare?
In this most recent community AI research paper reading, Arjun Mukerji, PhD – Staff Data Scientist at Atropos Health – walks us through RWESummary, a new benchmark designed to evaluate LLMs on summarizing real-world evidence from structured study output — an important but often under-tested scenario compared to the typical “summarize this PDF” task.
Learn more about AI observability and evaluation, join the Arize AI Slack community or get the latest on LinkedIn and X.
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By Arize AI
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Large language models are increasingly used to turn complex study output into plain-English summaries. But how do we know which models are safest and most reliable for healthcare?
In this most recent community AI research paper reading, Arjun Mukerji, PhD – Staff Data Scientist at Atropos Health – walks us through RWESummary, a new benchmark designed to evaluate LLMs on summarizing real-world evidence from structured study output — an important but often under-tested scenario compared to the typical “summarize this PDF” task.
Learn more about AI observability and evaluation, join the Arize AI Slack community or get the latest on LinkedIn and X.
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