A knowledge graph approach for the secondary use of cancer registry data

S. M. Shamimul Hasan; Donna Rivera; Xiao Cheng Wu; J. Blair Christian; Georgia Tourassi

doi:10.1109/BHI.2019.8834538

A knowledge graph approach for the secondary use of cancer registry data

S. M. Shamimul Hasan, Donna Rivera, Xiao Cheng Wu, J. Blair Christian, Georgia Tourassi

Computing & Computational Sciences Dir

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

3 Scopus citations

Abstract

Population-based central cancer registries collect valuable structured and unstructured cancer data primarily for surveillance and reporting. The collected data includes (1) categorization of each cancer case (tumor) at the time of diagnosis, (2) demographic information about the patient such as age, gender, and location at time of diagnosis, (3) first course of treatment information, and (4) survival outcomes when available. While advanced analytical approaches such as SEER∗Stat and SAS exist, we provide a knowledge graph approach to organizing cancer registry data for advanced analytics which offers unique advantages over existing approaches. This knowledge graph approach semantically enriches the data and enables straightforward linking capability with third-party data to help understand variation in cancer outcomes. A knowledge graph was developed using Louisiana Tumor Registry data. We present the advantages of the knowledge graph approach by examining: i) scenario-specific queries and ii) linkages with publicly available external datasets. Our results demonstrate this graph based solution can perform complex queries, improve query run-Time performance by 81%, and more easily conduct iterative analyses to enhance researchers understanding of cancer registry data.

Original language	English
Title of host publication	2019 IEEE EMBS International Conference on Biomedical and Health Informatics, BHI 2019 - Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781728108483
DOIs	https://doi.org/10.1109/BHI.2019.8834538
State	Published - May 2019
Event	2019 IEEE EMBS International Conference on Biomedical and Health Informatics, BHI 2019 - Chicago, United States Duration: May 19 2019 → May 22 2019

Publication series

Name	2019 IEEE EMBS International Conference on Biomedical and Health Informatics, BHI 2019 - Proceedings

Conference

Conference	2019 IEEE EMBS International Conference on Biomedical and Health Informatics, BHI 2019
Country/Territory	United States
City	Chicago
Period	05/19/19 → 05/22/19

Funding

V. ACKNOWLEDGMENT This work has been supported in part by the Joint Design of Advanced Computing Solutions for Cancer (JDACS4C) program established by the U.S. Department of Energy (DOE) and the National Cancer Institute (NCI) of National Institutes of Health. This work was performed under the auspices of the U.S. DOE by ANL under Contract DE-AC02-06-CH11357, LLNL under Contract DE-AC52-07NA27344, LANL under Contract DE-AC5206NA25396, and ORNL under Contract DE-AC05-00OR22725.

Keywords

Cancer registry
Knowledge graph
Treatment

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1109/BHI.2019.8834538

Cite this

Shamimul Hasan, S. M., Rivera, D., Wu, X. C., Christian, J. B., & Tourassi, G. (2019). A knowledge graph approach for the secondary use of cancer registry data. In 2019 IEEE EMBS International Conference on Biomedical and Health Informatics, BHI 2019 - Proceedings Article 8834538 (2019 IEEE EMBS International Conference on Biomedical and Health Informatics, BHI 2019 - Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/BHI.2019.8834538

Shamimul Hasan, S. M. ; Rivera, Donna ; Wu, Xiao Cheng et al. / A knowledge graph approach for the secondary use of cancer registry data. 2019 IEEE EMBS International Conference on Biomedical and Health Informatics, BHI 2019 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2019. (2019 IEEE EMBS International Conference on Biomedical and Health Informatics, BHI 2019 - Proceedings).

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abstract = "Population-based central cancer registries collect valuable structured and unstructured cancer data primarily for surveillance and reporting. The collected data includes (1) categorization of each cancer case (tumor) at the time of diagnosis, (2) demographic information about the patient such as age, gender, and location at time of diagnosis, (3) first course of treatment information, and (4) survival outcomes when available. While advanced analytical approaches such as SEER∗Stat and SAS exist, we provide a knowledge graph approach to organizing cancer registry data for advanced analytics which offers unique advantages over existing approaches. This knowledge graph approach semantically enriches the data and enables straightforward linking capability with third-party data to help understand variation in cancer outcomes. A knowledge graph was developed using Louisiana Tumor Registry data. We present the advantages of the knowledge graph approach by examining: i) scenario-specific queries and ii) linkages with publicly available external datasets. Our results demonstrate this graph based solution can perform complex queries, improve query run-Time performance by 81%, and more easily conduct iterative analyses to enhance researchers understanding of cancer registry data.",

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Shamimul Hasan, SM, Rivera, D, Wu, XC, Christian, JB & Tourassi, G 2019, A knowledge graph approach for the secondary use of cancer registry data. in 2019 IEEE EMBS International Conference on Biomedical and Health Informatics, BHI 2019 - Proceedings., 8834538, 2019 IEEE EMBS International Conference on Biomedical and Health Informatics, BHI 2019 - Proceedings, Institute of Electrical and Electronics Engineers Inc., 2019 IEEE EMBS International Conference on Biomedical and Health Informatics, BHI 2019, Chicago, United States, 05/19/19. https://doi.org/10.1109/BHI.2019.8834538

A knowledge graph approach for the secondary use of cancer registry data. / Shamimul Hasan, S. M.; Rivera, Donna; Wu, Xiao Cheng et al.
2019 IEEE EMBS International Conference on Biomedical and Health Informatics, BHI 2019 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2019. 8834538 (2019 IEEE EMBS International Conference on Biomedical and Health Informatics, BHI 2019 - Proceedings).

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

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AB - Population-based central cancer registries collect valuable structured and unstructured cancer data primarily for surveillance and reporting. The collected data includes (1) categorization of each cancer case (tumor) at the time of diagnosis, (2) demographic information about the patient such as age, gender, and location at time of diagnosis, (3) first course of treatment information, and (4) survival outcomes when available. While advanced analytical approaches such as SEER∗Stat and SAS exist, we provide a knowledge graph approach to organizing cancer registry data for advanced analytics which offers unique advantages over existing approaches. This knowledge graph approach semantically enriches the data and enables straightforward linking capability with third-party data to help understand variation in cancer outcomes. A knowledge graph was developed using Louisiana Tumor Registry data. We present the advantages of the knowledge graph approach by examining: i) scenario-specific queries and ii) linkages with publicly available external datasets. Our results demonstrate this graph based solution can perform complex queries, improve query run-Time performance by 81%, and more easily conduct iterative analyses to enhance researchers understanding of cancer registry data.

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Shamimul Hasan SM, Rivera D, Wu XC, Christian JB, Tourassi G. A knowledge graph approach for the secondary use of cancer registry data. In 2019 IEEE EMBS International Conference on Biomedical and Health Informatics, BHI 2019 - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2019. 8834538. (2019 IEEE EMBS International Conference on Biomedical and Health Informatics, BHI 2019 - Proceedings). doi: 10.1109/BHI.2019.8834538

A knowledge graph approach for the secondary use of cancer registry data

Abstract

Publication series

Conference

Funding

Keywords

UN SDGs

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