English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Automatically summarizing radiology reports into a concise impression canreduce the manual burden of clinicians and improve the consistency ofreporting. Previous work aimed to enhance content selection and factualitythrough guided abstractive summarization. However, two key issues persist.First, current methods heavily rely on domain-specific resources to extract theguidance signal, limiting their transferability to domains and languages wherethose resources are unavailable. Second, while automatic metrics like ROUGEshow progress, we lack a good understanding of the errors and failure modes inthis task. To bridge these gaps, we first propose a domain-agnostic guidancesignal in form of variable-length extractive summaries. Our empirical resultson two English benchmarks demonstrate that this guidance signal improves uponunguided summarization while being competitive with domain-specific methods.Additionally, we run an expert evaluation of four systems according to ataxonomy of 11 fine-grained errors. We find that the most pressing differencesbetween automatic summaries and those of radiologists relate to contentselection including omissions (up to 52%) and additions (up to 57%). Wehypothesize that latent reporting factors and corpus-level inconsistencies maylimit models to reliably learn content selection from the available data,presenting promising directions for future work.

Guidance in Radiology Report Summarization: An Empirical Evaluation and Error Analysis