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Evaluation of Large Language Models for Summarization Tasks in the Medical Domain: A Narrative Review
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Large Language Models have advanced clinical Natural Language Generation, creating opportunities to manage the volume of medical text. However, the high-stakes nature of medicine requires reliable evaluation, which remains a challenge. In this narrative review, we assess the current evaluation state for clinical summarization tasks and propose future directions to address the resource constraints of expert human evaluation.
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Cited by 2 Pith papers
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Development and Validation of the Provider Documentation Summarization Quality Instrument for Large Language Models
PDSQI-9 is a 9-item instrument for rating LLM-generated clinical summaries; in a validation study with 7 physician raters and 779 summary evaluations, it showed Cronbach's alpha 0.879 and ICC 0.867, but Krippendorff's...
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