A benchmark of 1,200 clinical documents shows three LLMs preserve diagnostic uncertainty expressions less than half the time and struggle with adjacent levels.
Large language models in the clinic: a comprehensive benchmark
4 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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2026 4verdicts
UNVERDICTED 4representative citing papers
EHRBench uses an EHR-LLM-KB pipeline to automatically create 960,067 reliable QA items spanning diagnosis, treatment, and prognosis for large-scale LLM evaluation in clinical decision making.
MedHarm benchmark shows aligned LLMs and guardrails can still produce unsafe responses on high-risk medical queries, indicating medical safety requires domain-specific testing.
Federated PEFT on LLMs across healthcare and finance datasets performs close to centralized training and beats isolated local training under non-IID conditions.
citing papers explorer
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Possible or Definite? A Benchmark for Evaluating Diagnostic Uncertainty Preservation in Clinical Text
A benchmark of 1,200 clinical documents shows three LLMs preserve diagnostic uncertainty expressions less than half the time and struggle with adjacent levels.
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EHRBench: An Automated and Reliable EHR-based Benchmark for Clinical Decision Making with LLMs
EHRBench uses an EHR-LLM-KB pipeline to automatically create 960,067 reliable QA items spanning diagnosis, treatment, and prognosis for large-scale LLM evaluation in clinical decision making.
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When Medical Safety Alignment Fails: A Benchmark for Evaluating LLMs on High-Risk Medical Queries
MedHarm benchmark shows aligned LLMs and guardrails can still produce unsafe responses on high-risk medical queries, indicating medical safety requires domain-specific testing.
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Towards the Next Frontier of LLMs, Training on Private Data: A Cross-Domain Benchmark for Federated Fine-Tuning
Federated PEFT on LLMs across healthcare and finance datasets performs close to centralized training and beats isolated local training under non-IID conditions.