Biomedical relation extraction using stochastic difference equations

Carl Tony Fakhry; Kourosh Zarringhalam; Ping Chen

doi:10.1109/HPEC.2015.7322474

Biomedical relation extraction using stochastic difference equations

Carl Tony Fakhry
, Kourosh Zarringhalam
, Ping Chen

University of Massachusetts Boston

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

Abstract

We propose an unsupervised method for extracting causal relations between biomedical entities using stochastic difference equations (SDE). Our method attempts to generalize the propagation of relevance in medical sentences in order to extract related biomedical terms and the semantic relation between them. We model the propagation of relevance in candidate medical sentences through the use of stochastic difference equations. The equation of propagation of relevance helps in identifying the most relevant medical terms in a causal sentence. It also increases the accuracy of Information Extraction as it allows to set a threshold for the minimum relevance for relation extraction.

Original language	English
Title of host publication	2015 IEEE High Performance Extreme Computing Conference, HPEC 2015
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781467392860
DOIs	https://doi.org/10.1109/HPEC.2015.7322474
State	Published - Nov 9 2015
Event	IEEE High Performance Extreme Computing Conference, HPEC 2015 - Waltham, United States Duration: Sep 15 2015 → Sep 17 2015

Publication series

Name	2015 IEEE High Performance Extreme Computing Conference, HPEC 2015

Conference

Conference	IEEE High Performance Extreme Computing Conference, HPEC 2015
Country/Territory	United States
City	Waltham
Period	9/15/15 → 9/17/15

ASJC Scopus Subject Areas

Computer Networks and Communications
Computer Science Applications
Information Systems

Access to Document

10.1109/HPEC.2015.7322474

Cite this

Fakhry, C. T., Zarringhalam, K., & Chen, P. (2015). Biomedical relation extraction using stochastic difference equations. In 2015 IEEE High Performance Extreme Computing Conference, HPEC 2015 Article 7322474 (2015 IEEE High Performance Extreme Computing Conference, HPEC 2015). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/HPEC.2015.7322474

Biomedical relation extraction using stochastic difference equations. / Fakhry, Carl Tony; Zarringhalam, Kourosh ; Chen, Ping.
2015 IEEE High Performance Extreme Computing Conference, HPEC 2015. Institute of Electrical and Electronics Engineers Inc., 2015. 7322474 (2015 IEEE High Performance Extreme Computing Conference, HPEC 2015).

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

Fakhry, CT, Zarringhalam, K & Chen, P 2015, Biomedical relation extraction using stochastic difference equations. in 2015 IEEE High Performance Extreme Computing Conference, HPEC 2015., 7322474, 2015 IEEE High Performance Extreme Computing Conference, HPEC 2015, Institute of Electrical and Electronics Engineers Inc., IEEE High Performance Extreme Computing Conference, HPEC 2015, Waltham, United States, 9/15/15. https://doi.org/10.1109/HPEC.2015.7322474

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AB - We propose an unsupervised method for extracting causal relations between biomedical entities using stochastic difference equations (SDE). Our method attempts to generalize the propagation of relevance in medical sentences in order to extract related biomedical terms and the semantic relation between them. We model the propagation of relevance in candidate medical sentences through the use of stochastic difference equations. The equation of propagation of relevance helps in identifying the most relevant medical terms in a causal sentence. It also increases the accuracy of Information Extraction as it allows to set a threshold for the minimum relevance for relation extraction.

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Biomedical relation extraction using stochastic difference equations

Abstract

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Conference

ASJC Scopus Subject Areas

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