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Automatic ICD Code Assignment to Medical Text with Semantic Relational Tuples

Zhao, Sanqiang and He, Daqing and Zhang, Danchen and Li, Lei and Meng, Rui (2016) Automatic ICD Code Assignment to Medical Text with Semantic Relational Tuples. In: IConference 2017, 22 March 2017 - 25 March 2017, Wuhan, China.

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Abstract

Mining the Electronic Medical Record (EMR henceforth) is growing in popularity but still lacks good methods for better understanding the text in EMR. One important task is assigning proper International Classification of Diseases (ICD henceforth, which is the code schema for EMR) code based on the narrative text of EMR document. For the task, we propose an automatic feature extraction method by means of capturing semantic relational tuples. We proved the semantic relational tuple is able to capture information at semantic level and it contribute to ICD-9 classification task in two aspects, negation identification and feature generation.


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Details

Item Type: Conference or Workshop Item (Poster)
Creators/Authors:
CreatorsEmailPitt UsernameORCID
Zhao, Sanqiangsaz31@pitt.eduSAZ31
He, Daqingdah44@pitt.eduDAH44
Zhang, Danchendaz45@pitt.eduDAZ45
Li, Lei
Meng, Rui
Date: September 2016
Date Type: Publication
Event Title: IConference 2017
Event Dates: 22 March 2017 - 25 March 2017
Event Type: Conference
Schools and Programs: School of Information Sciences > Information Science
Refereed: Yes
Date Deposited: 19 Jun 2017 14:26
Last Modified: 01 Nov 2017 14:01
URI: http://d-scholarship.pitt.edu/id/eprint/32398

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  • Automatic ICD Code Assignment to Medical Text with Semantic Relational Tuples. (deposited 19 Jun 2017 14:26) [Currently Displayed]

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