Evaluating Large Language Models for Drafting Emergency Department Discharge Summaries is a research paper published in medRxiv (2024). On theSindex it has a DataRank of 1.9. It has been cited 35 times, with 29 citing works in its 1-hop citation network.
Scored on demand from live citation data
Linked data & code
DataRank reads this dataset's downstream impact straight off the citation graph β no black box, no proprietary weighting. How is this computed?
FAIR checklist signals are shown for context only and do not affect DataRank scoring.
We only score data papers we can read in full β never from an abstract alone.
Base Score Contribution
0.538
From this paper's citation signal
Citation Network Contribution
1.4
From 23 citing papers with measurable signal
National Institutes of Health
Grant: 5K23HD110716-02
Accurate and Reliable Diagnostics for Injured Children: Machine Learning for Ultrasound
NICHD NIH HHS
Grant: K23 HD110716
Fields of Study
Keywords
Sustainable Development Goals
Additional file 1 of A pilot feasibility study comparing large language models in extracting key information from ICU patient text records from an Irish population
Additional file 1 of A pilot feasibility study comparing large language models in extracting key information from ICU patient text records from an Irish population