mlsanityData to 7 Oct 2026

A preliminary study on evaluating Consultation Notes with Post-Editing

arXiv 2104.04402 ↗First posted 9 Apr 2021cs.CLcited by 10

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Abstract (arXiv)

Automatic summarisation has the potential to aid physicians in streamlining clerical tasks such as note taking. But it is notoriously difficult to evaluate these systems and demonstrate that they are safe to be used in a clinical setting. To circumvent this issue, we propose a semi-automatic approach whereby physicians post-edit generated notes before submitting them. We conduct a preliminary study on the time saving of automatically generated consultation notes with post-editing. Our evaluators are asked to listen to mock consultations and to post-edit three generated notes. We time this and find that it is faster than writing the note from scratch. We present insights and lessons learnt from this experiment.

Key facts. Cited by 10 papers in the map (data through 7 Oct 2026). Builds on 1 of its 19 references that are in the map. First posted on arXiv 9 Apr 2021.

Builds on

1 of 19 references.

References · 1

  1. 2019BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehensioncited by 5,874

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Cited by year

Citing papers per year: 2022: 4; 2023: 2; 2024: 1; 2025: 3.

10 papers.