research-article

Effects of Mining Parameters on the Performance of the Sequence Pattern Variants Analyzing Method Applied to Electronic Medical Record Systems

Authors:

Tatsuhiro Yamada,

Masaaki Kayahara,

Haruo YokotaAuthors Info & Claims

iiWAS2019: Proceedings of the 21st International Conference on Information Integration and Web-based Applications & Services

Pages 127 - 135

https://doi.org/10.1145/3366030.3366074

Published: 22 February 2020 Publication History

Abstract

Sequential pattern mining (SPM) is widely used for data mining and knowledge discovery in various application domains. Recently, we have proposed an analyzing method to evaluate the sequence pattern variant (SPV) that is the original sequence containing frequent patterns including variants. Such a study is meaningful for medical tasks such as improving the quality of a disease's treatment method. This paper aims to evaluate the effectiveness of the proposed analyzing method in more detail when it was applied to Electronic Medical Record Systems. Using a real dataset, it is observed that the analyzing method is successful in statistically discovering the meaningful indicators that are leading to the difference between comparative SPVs, such as complicated risk, severity risk of the disease, the length of stay in the hospital and the total medical cost. Moreover, it is observed that the length of stay and the medical cost can gain more benefit from increasing the significance level parameter used in comparing the SPVs.

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Cited By

Le HYasumitsu YMatsuo RYamazaki TYokota H(2024)A Clustering-based Sequence Variants Analysis Method for Electronic Medical Records of Multimedical Institutions2024 IEEE 7th International Conference on Multimedia Information Processing and Retrieval (MIPR)10.1109/MIPR62202.2024.00113(653-659)Online publication date: 7-Aug-2024
https://doi.org/10.1109/MIPR62202.2024.00113
Kushima MMatsuo ROgawa TAraki KHasegawa YNozue SOkazaki EKoga H(2020)Development of Patient Information Extraction Method by Sequence Labeling using Electronic Medical Records2020 IEEE 50th International Symposium on Multiple-Valued Logic (ISMVL)10.1109/ISMVL49045.2020.00-21(105-110)Online publication date: Nov-2020
https://doi.org/10.1109/ISMVL49045.2020.00-21

Index Terms

Effects of Mining Parameters on the Performance of the Sequence Pattern Variants Analyzing Method Applied to Electronic Medical Record Systems
1. Information systems
  1. Information systems applications
    1. Data mining

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cover image ACM Other conferences

iiWAS2019: Proceedings of the 21st International Conference on Information Integration and Web-based Applications & Services

December 2019

709 pages

ISBN:9781450371797

DOI:10.1145/3366030

Copyright © 2019 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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JKU: Johannes Kepler Universität Linz
@WAS: International Organization of Information Integration and Web-based Applications and Services

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 22 February 2020

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iiWAS2019: The 21st International Conference on Information Integration and Web-based Applications & Services

December 2 - 4, 2019

Munich, Germany

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Cited By

Le HYasumitsu YMatsuo RYamazaki TYokota H(2024)A Clustering-based Sequence Variants Analysis Method for Electronic Medical Records of Multimedical Institutions2024 IEEE 7th International Conference on Multimedia Information Processing and Retrieval (MIPR)10.1109/MIPR62202.2024.00113(653-659)Online publication date: 7-Aug-2024
https://doi.org/10.1109/MIPR62202.2024.00113
Kushima MMatsuo ROgawa TAraki KHasegawa YNozue SOkazaki EKoga H(2020)Development of Patient Information Extraction Method by Sequence Labeling using Electronic Medical Records2020 IEEE 50th International Symposium on Multiple-Valued Logic (ISMVL)10.1109/ISMVL49045.2020.00-21(105-110)Online publication date: Nov-2020
https://doi.org/10.1109/ISMVL49045.2020.00-21

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