Physician oversight reveals high error rates in LLM-generated labels for a clinical benchmark and demonstrates that corrected labels improve both evaluation accuracy and downstream model training.
Large language models for preventing medication direction errors in online pharmacies
3 Pith papers cite this work. Polarity classification is still indexing.
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DrugRAG improves LLM accuracy on pharmacy questions by 7-21 percentage points by retrieving structured drug information and augmenting prompts.
This review summarizes how large language models are being used for workflow automation, clinical decision support, and patient engagement in radiation oncology.
citing papers explorer
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Scalable Stewardship of an LLM-Assisted Clinical Benchmark with Physician Oversight
Physician oversight reveals high error rates in LLM-generated labels for a clinical benchmark and demonstrates that corrected labels improve both evaluation accuracy and downstream model training.
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DrugRAG: Enhancing Pharmacy LLM Performance Through A Novel Retrieval-Augmented Generation Pipeline
DrugRAG improves LLM accuracy on pharmacy questions by 7-21 percentage points by retrieving structured drug information and augmenting prompts.
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Applications of Large Language Models in Radiation Oncology: From Workflow Automation to Clinical Intelligence
This review summarizes how large language models are being used for workflow automation, clinical decision support, and patient engagement in radiation oncology.