Community Paper Reading: RWESummary: A Framework and Test for Choosing Large Language Models to Summarize Real-World Evidence (RWE) Studies

​Join our upcoming community paper reading, where we'll dive into "RWESummary: A Framework and Test for Choosing Large Language Models to Summarize Real-World Evidence (RWE) Studies."

LLMs have been extensively evaluated for general summarization tasks as well as medical research assistance, but they have not been specifically evaluated for the task of summarizing real-world evidence from structured output of RWE studies. This paper introduces RWESummary, a proposed addition to the MedHELM framework (Bedi, Cui, Fuentes, Unell et al., 2025) to enable benchmarking of LLMs for this task. 

We're thrilled to host the paper's lead author, Arjun Mukerji, PhD, Staff Data Scientist at Atropos Health, who will walk us through the research and its implications. Following the presentation, there will be a live Q&A session, so bring your questions!

Read the paper: https://www.atroposhealth.com/rwesummary-a-framework-and-test-for-choosing-large-language-models-to-summarize-real-world-evidence-rwe-studies/