somewordstoolate/Q2CRBench-3
Q2CRBench-3 Q2CRBench-3 is a benchmark dataset designed to evaluate the performance of LLM in generating clinical recommendations. It is derived from the development records of three authoritative clinical guidelines: the 2020 EAN guideline for dementia, the 2021 ACR guideline for rheumatoid arthritis, and the 2024 KDIGO guideline for chronic kidney disease. Due to copyright restrictions, we are unable to provide the screened records from the 2020 EAN Dementia and 2021 ACR RA… See the full description on the dataset page: https://huggingface.co/datasets/somewordstoolate/Q2CRBench-3.
Q2CRBench-3
Q2CRBench-3 is a benchmark dataset designed to evaluate the performance of LLM in generating clinical recommendations. It is derived from the development records of three authoritative clinical guidelines: the 2020 EAN guideline for dementia, the 2021 ACR guideline for rheumatoid arthritis, and the 2024 KDIGO guideline for chronic kidney disease00766-4/fulltext).
Due to copyright restrictions, we are unable to provide the screened records from the 2020 EAN Dementia and 2021 ACR RA datasets directly. However, you can reproduce them by applying the corresponding search strategies or sending request to us (see here for more details). We separate evidence profiles into Outcome and Paper two parts, you can assess its raw data version in Quicker Repository if necessary.
More details can be find:
- Repository: Quicker Repository
- Published Article: Streamlining Evidence Based Clinical Recommendations with Large Language Models