A study of convolutional neural networks for clinical document classification in systematic reviews: Sysreview at CLEF eHealth 2017

Identifying eligible documents for systematic reviews is one of the most time-consuming steps in writing the reviews. From retrieving numerous clinical documents to manually checking the documents with detailed criteria requires a tremendous amount of time and skilled workforce. In this paper, to in...

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Main Author:	Lee, Grace Eunkyung
Other Authors:	School of Computer Science and Engineering
Format:	Article
Language:	English
Published:	2018
Subjects:	Document Classification Systematic Review
Online Access:	https://hdl.handle.net/10356/89461 http://hdl.handle.net/10220/44958
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Institution:	Nanyang Technological University
Language:	English

id	sg-ntu-dr.10356-89461
record_format	dspace
spelling	sg-ntu-dr.10356-894612019-12-06T17:26:01Z A study of convolutional neural networks for clinical document classification in systematic reviews: Sysreview at CLEF eHealth 2017 Lee, Grace Eunkyung School of Computer Science and Engineering Document Classification Systematic Review Identifying eligible documents for systematic reviews is one of the most time-consuming steps in writing the reviews. From retrieving numerous clinical documents to manually checking the documents with detailed criteria requires a tremendous amount of time and skilled workforce. In this paper, to increase the efficiency of the process we examine the role of convolutional neural networks for classifying medical documents for systematic reviews. The analysis is carried out in the context of the CLEF 2017 eHealth Task 2 as a participant. The evaluation demonstrates that the suggested methods show slightly better performance for full document screening than abstract screening. Published version 2018-06-05T08:38:00Z 2019-12-06T17:26:01Z 2018-06-05T08:38:00Z 2019-12-06T17:26:01Z 2017 Journal Article Lee, G. E. (2017). A Study of Convolutional Neural Networks for Clinical Document Classification in Systematic Reviews: SysReview at CLEF eHealth 2017. CEUR Workshop Proceedings. 1613-0073 https://hdl.handle.net/10356/89461 http://hdl.handle.net/10220/44958 en CEUR Workshop Proceedings © 2017 The Author(s). This paper was published in CEUR Workshop Proceedings and is made available as an electronic reprint (preprint) with permission of The Author(s). The published version is available at: [http://ceur-ws.org/Vol-1866/paper_88.pdf]. One print or electronic copy may be made for personal use only. Systematic or multiple reproduction, distribution to multiple locations via electronic or other means, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper is prohibited and is subject to penalties under law. 7 p. application/pdf
institution	Nanyang Technological University
building	NTU Library
country	Singapore
collection	DR-NTU
language	English
topic	Document Classification Systematic Review
spellingShingle	Document Classification Systematic Review Lee, Grace Eunkyung A study of convolutional neural networks for clinical document classification in systematic reviews: Sysreview at CLEF eHealth 2017
description	Identifying eligible documents for systematic reviews is one of the most time-consuming steps in writing the reviews. From retrieving numerous clinical documents to manually checking the documents with detailed criteria requires a tremendous amount of time and skilled workforce. In this paper, to increase the efficiency of the process we examine the role of convolutional neural networks for classifying medical documents for systematic reviews. The analysis is carried out in the context of the CLEF 2017 eHealth Task 2 as a participant. The evaluation demonstrates that the suggested methods show slightly better performance for full document screening than abstract screening.
author2	School of Computer Science and Engineering
author_facet	School of Computer Science and Engineering Lee, Grace Eunkyung
format	Article
author	Lee, Grace Eunkyung
author_sort	Lee, Grace Eunkyung
title	A study of convolutional neural networks for clinical document classification in systematic reviews: Sysreview at CLEF eHealth 2017
title_short	A study of convolutional neural networks for clinical document classification in systematic reviews: Sysreview at CLEF eHealth 2017
title_full	A study of convolutional neural networks for clinical document classification in systematic reviews: Sysreview at CLEF eHealth 2017
title_fullStr	A study of convolutional neural networks for clinical document classification in systematic reviews: Sysreview at CLEF eHealth 2017
title_full_unstemmed	A study of convolutional neural networks for clinical document classification in systematic reviews: Sysreview at CLEF eHealth 2017
title_sort	study of convolutional neural networks for clinical document classification in systematic reviews: sysreview at clef ehealth 2017
publishDate	2018
url	https://hdl.handle.net/10356/89461 http://hdl.handle.net/10220/44958
_version_	1681049777415913472

A study of convolutional neural networks for clinical document classification in systematic reviews: Sysreview at CLEF eHealth 2017

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