23 citations · 65 across the 13 of their papers we have counts for
17 papers
Caught in the Web of Words: Do LLMs Fall for Spin in Medical Literature?
Hye Sun Yun, Karen Y. C. Zhang, Ramez Kouzy +3
Medical research faces well-documented challenges in translating novel treatments into clinical practice. Publishing incentives encourage researchers to present "positive" findings…
Automatically Extracting Numerical Results from Randomized Controlled Trials with Large Language Models
Hye Sun Yun, David Pogrebitskiy, Iain J. Marshall +1
Meta-analyses statistically aggregate the findings of different randomized controlled trials (RCTs) to assess treatment effectiveness. Because this yields robust estimates of treat…
Summarizing, Simplifying, and Synthesizing Medical Evidence Using GPT-3 (with Varying Success)
Chantal Shaib, Millicent L. Li, Sebastian Joseph +3
Large language models, particularly GPT-3, are able to produce high quality summaries of general domain news articles in few- and zero-shot settings. However, it is unclear if such…
Appraising the Potential Uses and Harms of LLMs for Medical Systematic Reviews
Hye Sun Yun, Iain J. Marshall, Thomas A. Trikalinos +1
Medical systematic reviews play a vital role in healthcare decision making and policy. However, their production is time-consuming, limiting the availability of high-quality and up…
Do Multi-Document Summarization Models Synthesize?
Jay DeYoung, Stephanie C. Martinez, Iain J. Marshall +1
Multi-document summarization entails producing concise synopses of collections of inputs. For some applications, the synopsis should accurately synthesize inputs with respect to a…
What Would it Take to get Biomedical QA Systems into Practice?
Gregory Kell, Iain J. Marshall, Byron C. Wallace +1
Medical question answering (QA) systems have the potential to answer clinicians uncertainties about treatment and diagnosis on demand, informed by the latest evidence. However, des…