Mapping Common Data Elements to a Domain Model Using an Artificial Neural Network

Robinette Renner, Shengyu Li, Yulong Huang, Shaobo Tan, Dongqi Li, Ada Chaeli Van Der Zijp-Tan, Ryan Benton, Glen M. Borchert, Jingshan Huang, Guoqian D Jiang

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

1 Scopus citations

Abstract

The medical community uses a variety of data standards for clinical and research reporting needs. ISO 11179 Common Data Elements (CDEs) is one such standard that provides robust data point definitions. The Biomedical Research Integrated Domain Group (BRIDG) model is a domain analysis model that provides a contextual framework for biomedical and clinical research data. Manually mapping the CDEs to the BRIDG model can facilitate mapping the CDEs to other standards. Unfortunately, the error-prone, labor-intensive manual mapping process creates a significant barrier for researchers who use CDEs. In this paper, we present our preliminary work to develop a semi-automated algorithm to map CDEs to likely BRIDG classes. First, we extended and improved our previously developed artificial neural network (ANN) alignment algorithm. We then used a collection of 1,284 CDEs mapped to BRIDG classes as the gold standard to train and obtain the appropriate weights of six CDE attributes. Finally, we recommended a list of candidate BRIDG classes to which the CDE of interest may belong. Preliminary testing has proven the effectiveness and efficiency of our proposed methodology in mapping CDEs to BRIDG classes.

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.
Pages1532-1535
Number of pages4
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

Keywords

  • artificial neural network (ANN)
  • Biomedical Research Integrated Domain Group (BRIDG) model
  • common data element (CDE)
  • schema mapping

ASJC Scopus subject areas

  • Biomedical Engineering
  • Health Informatics

Fingerprint Dive into the research topics of 'Mapping Common Data Elements to a Domain Model Using an Artificial Neural Network'. Together they form a unique fingerprint.

  • Cite this

    Renner, R., Li, S., Huang, Y., Tan, S., Li, D., Zijp-Tan, A. C. V. D., Benton, R., Borchert, G. M., Huang, J., & Jiang, G. D. (2019). Mapping Common Data Elements to a Domain Model Using an Artificial Neural Network. 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. 1532-1535). [8621535] (Proceedings - 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/BIBM.2018.8621535