Temporal sequence alignment in electronic health records for computable patient representation

Ming Huang, Maryam Zolnoori, Nilay D Shah, Lixia Yao

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

Constructing patient representation from EHRs has become an emerging hot research topic, as it is widely used for predicting disease prognosis, medication outcomes and mortality, and identifying patients who are similar to a target patient. Sequence alignment methods are able to preserve the temporal sequence information in patient medical records when constructing computable patient representation and thus are worth comprehensive and objective evaluation. In this work, we synthesized patient medical records using a set of synthesis operations on top of real patient medical records from a large real-world EHR database. Then we tested two cutting-edge sequence alignment methods, namely dynamic time warping (DTW) and Needleman-Wunsch algorithm (NWA) for the purpose of patient medical records alignment, in order to understand their strengths and limitations. Our results show that both DTW and NWA outperform the reference alignment. DTW seems to align better than NWA by inserting new daily events and identifying more similarities between patient medical records. By incorporating medical knowledge, we can improve the temporal sequence alignment by these algorithms even better and create more accurate patient representation for predictive models and patient similarity calculation.

Original languageEnglish (US)
Title of host publicationProceedings - 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018
EditorsHarald Schmidt, David Griol, Haiying Wang, Jan Baumbach, Huiru Zheng, Zoraida Callejas, Xiaohua Hu, Julie Dickerson, Le Zhang
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1054-1061
Number of pages8
ISBN (Electronic)9781538654880
DOIs
StatePublished - Jan 21 2019
Event2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018 - Madrid, Spain
Duration: Dec 3 2018Dec 6 2018

Publication series

NameProceedings - 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018

Conference

Conference2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018
CountrySpain
CityMadrid
Period12/3/1812/6/18

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Keywords

  • dynamic time warping
  • electronic health record
  • needleman-Wunsch algorithm
  • patient representation
  • patient similarity
  • sequence alignment method
  • temporal sequence

ASJC Scopus subject areas

  • Biomedical Engineering
  • Health Informatics

Cite this

Huang, M., Zolnoori, M., Shah, N. D., & Yao, L. (2019). Temporal sequence alignment in electronic health records for computable patient representation. In H. Schmidt, D. Griol, H. Wang, J. Baumbach, H. Zheng, Z. Callejas, X. Hu, J. Dickerson, & L. Zhang (Eds.), Proceedings - 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018 (pp. 1054-1061). [8621428] (Proceedings - 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/BIBM.2018.8621428