COVID Vaccine and Cardiovascular Risks: A Natural Language Analysis of Vaccine Adverse Event Reports

Yiqing Zhao; Michael G. Ison; Yuan Luo

doi:10.1109/BIBM52615.2021.9669540

COVID Vaccine and Cardiovascular Risks: A Natural Language Analysis of Vaccine Adverse Event Reports

Yiqing Zhao, Michael G. Ison, Yuan Luo^*

^*Corresponding author for this work

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

Abstract

Adverse events (AEs) following COVID vaccination have been intensely monitored. In our study, we developed a natural language processing system to analyze data from a spontaneous reporting system - Vaccine Adverse Event Reporting System and detect signals of AEs following administration of COVID vaccines. Our system included several components to magnify novel and rare AEs, including 1) excluding COVID positive patients, 2) excluding sentences discussing disease history or family history, 3) standardizing symptom concepts into 30 major AEs, 4) using influenza vaccine recipients as control group when calculating reporting odds ratio. We identified several cardiovascular and inflammatory-related AEs that demonstrated high odds ratio. We demonstrated our system can serve as a complementary system to identify and monitor AEs outside of pre-defined outcomes routinely monitored by existing databases or projects.

Original language	English (US)
Title of host publication	Proceedings - 2021 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2021
Editors	Yufei Huang, Lukasz Kurgan, Feng Luo, Xiaohua Tony Hu, Yidong Chen, Edward Dougherty, Andrzej Kloczkowski, Yaohang Li
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	614-618
Number of pages	5
ISBN (Electronic)	9781665401265
DOIs	https://doi.org/10.1109/BIBM52615.2021.9669540
State	Published - 2021
Event	2021 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2021 - Virtual, Online, United States Duration: Dec 9 2021 → Dec 12 2021

Publication series

Name	Proceedings - 2021 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2021

Conference

Conference	2021 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2021
Country/Territory	United States
City	Virtual, Online
Period	12/9/21 → 12/12/21

Keywords

COVID vaccine
concept standardization
natural language processing
rare adverse event

ASJC Scopus subject areas

Artificial Intelligence
Computer Science Applications
Biomedical Engineering
Health Informatics
Information Systems and Management

UN SDGs

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

Access to Document

10.1109/BIBM52615.2021.9669540

Cite this

Zhao, Y., Ison, M. G., & Luo, Y. (2021). COVID Vaccine and Cardiovascular Risks: A Natural Language Analysis of Vaccine Adverse Event Reports. In Y. Huang, L. Kurgan, F. Luo, X. T. Hu, Y. Chen, E. Dougherty, A. Kloczkowski, & Y. Li (Eds.), Proceedings - 2021 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2021 (pp. 614-618). (Proceedings - 2021 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2021). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/BIBM52615.2021.9669540

Zhao, Yiqing ; Ison, Michael G. ; Luo, Yuan. / COVID Vaccine and Cardiovascular Risks : A Natural Language Analysis of Vaccine Adverse Event Reports. Proceedings - 2021 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2021. editor / Yufei Huang ; Lukasz Kurgan ; Feng Luo ; Xiaohua Tony Hu ; Yidong Chen ; Edward Dougherty ; Andrzej Kloczkowski ; Yaohang Li. Institute of Electrical and Electronics Engineers Inc., 2021. pp. 614-618 (Proceedings - 2021 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2021).

@inproceedings{c040803aad884f809f1e6fad9fdf9dd9,

title = "COVID Vaccine and Cardiovascular Risks: A Natural Language Analysis of Vaccine Adverse Event Reports",

abstract = "Adverse events (AEs) following COVID vaccination have been intensely monitored. In our study, we developed a natural language processing system to analyze data from a spontaneous reporting system - Vaccine Adverse Event Reporting System and detect signals of AEs following administration of COVID vaccines. Our system included several components to magnify novel and rare AEs, including 1) excluding COVID positive patients, 2) excluding sentences discussing disease history or family history, 3) standardizing symptom concepts into 30 major AEs, 4) using influenza vaccine recipients as control group when calculating reporting odds ratio. We identified several cardiovascular and inflammatory-related AEs that demonstrated high odds ratio. We demonstrated our system can serve as a complementary system to identify and monitor AEs outside of pre-defined outcomes routinely monitored by existing databases or projects.",

keywords = "COVID vaccine, concept standardization, natural language processing, rare adverse event",

author = "Yiqing Zhao and Ison, {Michael G.} and Yuan Luo",

note = "Funding Information: The work is supported in part R01LM013337 and U01TR003528. Publisher Copyright: {\textcopyright} 2021 IEEE.; 2021 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2021 ; Conference date: 09-12-2021 Through 12-12-2021",

year = "2021",

doi = "10.1109/BIBM52615.2021.9669540",

language = "English (US)",

series = "Proceedings - 2021 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2021",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "614--618",

editor = "Yufei Huang and Lukasz Kurgan and Feng Luo and Hu, {Xiaohua Tony} and Yidong Chen and Edward Dougherty and Andrzej Kloczkowski and Yaohang Li",

booktitle = "Proceedings - 2021 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2021",

address = "United States",

}

Zhao, Y, Ison, MG & Luo, Y 2021, COVID Vaccine and Cardiovascular Risks: A Natural Language Analysis of Vaccine Adverse Event Reports. in Y Huang, L Kurgan, F Luo, XT Hu, Y Chen, E Dougherty, A Kloczkowski & Y Li (eds), Proceedings - 2021 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2021. Proceedings - 2021 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2021, Institute of Electrical and Electronics Engineers Inc., pp. 614-618, 2021 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2021, Virtual, Online, United States, 12/9/21. https://doi.org/10.1109/BIBM52615.2021.9669540

COVID Vaccine and Cardiovascular Risks : A Natural Language Analysis of Vaccine Adverse Event Reports. / Zhao, Yiqing; Ison, Michael G.; Luo, Yuan.

Proceedings - 2021 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2021. ed. / Yufei Huang; Lukasz Kurgan; Feng Luo; Xiaohua Tony Hu; Yidong Chen; Edward Dougherty; Andrzej Kloczkowski; Yaohang Li. Institute of Electrical and Electronics Engineers Inc., 2021. p. 614-618 (Proceedings - 2021 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2021).

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

TY - GEN

T1 - COVID Vaccine and Cardiovascular Risks

T2 - 2021 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2021

AU - Zhao, Yiqing

AU - Ison, Michael G.

AU - Luo, Yuan

PY - 2021

Y1 - 2021

N2 - Adverse events (AEs) following COVID vaccination have been intensely monitored. In our study, we developed a natural language processing system to analyze data from a spontaneous reporting system - Vaccine Adverse Event Reporting System and detect signals of AEs following administration of COVID vaccines. Our system included several components to magnify novel and rare AEs, including 1) excluding COVID positive patients, 2) excluding sentences discussing disease history or family history, 3) standardizing symptom concepts into 30 major AEs, 4) using influenza vaccine recipients as control group when calculating reporting odds ratio. We identified several cardiovascular and inflammatory-related AEs that demonstrated high odds ratio. We demonstrated our system can serve as a complementary system to identify and monitor AEs outside of pre-defined outcomes routinely monitored by existing databases or projects.

AB - Adverse events (AEs) following COVID vaccination have been intensely monitored. In our study, we developed a natural language processing system to analyze data from a spontaneous reporting system - Vaccine Adverse Event Reporting System and detect signals of AEs following administration of COVID vaccines. Our system included several components to magnify novel and rare AEs, including 1) excluding COVID positive patients, 2) excluding sentences discussing disease history or family history, 3) standardizing symptom concepts into 30 major AEs, 4) using influenza vaccine recipients as control group when calculating reporting odds ratio. We identified several cardiovascular and inflammatory-related AEs that demonstrated high odds ratio. We demonstrated our system can serve as a complementary system to identify and monitor AEs outside of pre-defined outcomes routinely monitored by existing databases or projects.

KW - COVID vaccine

KW - concept standardization

KW - natural language processing

KW - rare adverse event

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UR - http://www.scopus.com/inward/citedby.url?scp=85125172883&partnerID=8YFLogxK

U2 - 10.1109/BIBM52615.2021.9669540

DO - 10.1109/BIBM52615.2021.9669540

M3 - Conference contribution

AN - SCOPUS:85125172883

T3 - Proceedings - 2021 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2021

SP - 614

EP - 618

BT - Proceedings - 2021 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2021

A2 - Huang, Yufei

A2 - Kurgan, Lukasz

A2 - Luo, Feng

A2 - Hu, Xiaohua Tony

A2 - Chen, Yidong

A2 - Dougherty, Edward

A2 - Kloczkowski, Andrzej

A2 - Li, Yaohang

PB - Institute of Electrical and Electronics Engineers Inc.

Y2 - 9 December 2021 through 12 December 2021

ER -

Zhao Y, Ison MG, Luo Y. COVID Vaccine and Cardiovascular Risks: A Natural Language Analysis of Vaccine Adverse Event Reports. In Huang Y, Kurgan L, Luo F, Hu XT, Chen Y, Dougherty E, Kloczkowski A, Li Y, editors, Proceedings - 2021 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2021. Institute of Electrical and Electronics Engineers Inc. 2021. p. 614-618. (Proceedings - 2021 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2021). doi: 10.1109/BIBM52615.2021.9669540

COVID Vaccine and Cardiovascular Risks: A Natural Language Analysis of Vaccine Adverse Event Reports

Abstract

Publication series

Conference

Keywords

ASJC Scopus subject areas

UN SDGs

Access to Document

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