Automated text summarisation and evidence-based medicine: a survey of two domains

Abeed Sarker, Diego Molla, Cecile Paris

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

Abstract

The practice of evidence-based medicine (EBM) urges medical practitioners to utilise the latest research evidence when making clinical decisions. Because of the massive and growing volume of published research on various medical topics, practitioners often find themselves overloaded with information. As such, natural language processing research has recently commenced exploring techniques for performing medical domain-specific automated text summarisation (ATS) techniques-- targeted towards the task of condensing large medical texts. However, the development of effective summarisation techniques for this task requires cross-domain knowledge. We present a survey of EBM, the domain-specific needs for EBM, automated summarisation techniques, and how they have been applied hitherto. We envision that this survey will serve as a first resource for the development of future operational text summarisation techniques for EBM.
LanguageEnglish
Title of host publicationArxiv.org pre-prints
Number of pages35
Publication statusSubmitted - 25 Jun 2017

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Sarker, A., Molla, D., & Paris, C. (2017). Automated text summarisation and evidence-based medicine: a survey of two domains. Manuscript submitted for publication. In Arxiv.org pre-prints
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Automated text summarisation and evidence-based medicine : a survey of two domains. / Sarker, Abeed; Molla, Diego; Paris, Cecile.

Arxiv.org pre-prints. 2017.

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

TY - GEN

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AB - The practice of evidence-based medicine (EBM) urges medical practitioners to utilise the latest research evidence when making clinical decisions. Because of the massive and growing volume of published research on various medical topics, practitioners often find themselves overloaded with information. As such, natural language processing research has recently commenced exploring techniques for performing medical domain-specific automated text summarisation (ATS) techniques-- targeted towards the task of condensing large medical texts. However, the development of effective summarisation techniques for this task requires cross-domain knowledge. We present a survey of EBM, the domain-specific needs for EBM, automated summarisation techniques, and how they have been applied hitherto. We envision that this survey will serve as a first resource for the development of future operational text summarisation techniques for EBM.

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