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Evaluation of Large Language Models for Summarization Tasks in the Medical Domain: A Narrative Review

Computation and Language 2024-09-30 v1 Artificial Intelligence

Abstract

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.

Keywords

Cite

@article{arxiv.2409.18170,
  title  = {Evaluation of Large Language Models for Summarization Tasks in the Medical Domain: A Narrative Review},
  author = {Emma Croxford and Yanjun Gao and Nicholas Pellegrino and Karen K. Wong and Graham Wills and Elliot First and Frank J. Liao and Cherodeep Goswami and Brian Patterson and Majid Afshar},
  journal= {arXiv preprint arXiv:2409.18170},
  year   = {2024}
}