Extractive evidence based medicine summarisation based on sentence-specific statistics

Abeed Sarker*, Diego Mollá, Cécile Paris

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contribution

1 Citation (Scopus)

Abstract

We present an approach for extracting 3-sentence evidence-based summaries relevant to clinical questions. We approach this task as one of query-focused, extractive, single-document summarisation using sentence-specific statistics for each target sentence. We incorporate simple statistics and domain knowledge and show that such an approach is effective for identifying informative sentences from medical abstracts. Our system is evaluated automatically using ROUGE, and we compare our results with several baselines. The ROUGE-L F-scores of our system outperform all baselines. In addition, our approach is computationally efficient, and, on a percentile rank measure, our system achieves a percentile rank of 97.3%.

Original languageEnglish
Title of host publicationProceedings of the 25th IEEE International Symposium on Computer-Based Medical Systems, CBMS 2012
EditorsPaolo Soda, Francesco Tortorella
Place of PublicationPiscataway, NJ
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages1-4
Number of pages4
ISBN (Print)9781467320511
DOIs
Publication statusPublished - 2012
Event25th IEEE International Symposium on Computer-Based Medical Systems, CBMS 2012 - Rome, Italy
Duration: 20 Jun 201222 Jun 2012

Other

Other25th IEEE International Symposium on Computer-Based Medical Systems, CBMS 2012
CountryItaly
CityRome
Period20/06/1222/06/12

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