This paper is in the following e-collection/theme issue:

Natural Language Processing (692) Infodemiology and Infoveillance (1349) Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (1041) Machine Learning (1465) Medicine 2.0: Social Media, Open, Participatory, Collaborative Medicine (1641) Infoveillance and Social Listening (209) Ontologies, Classifications, and Coding (239)

Published on in Vol 9, No 11 (2021): November

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/29768, first published .
A Pipeline to Understand Emerging Illness Via Social Media Data Analysis: Case Study on Breast Implant Illness

A Pipeline to Understand Emerging Illness Via Social Media Data Analysis: Case Study on Breast Implant Illness

A Pipeline to Understand Emerging Illness Via Social Media Data Analysis: Case Study on Breast Implant Illness

Authors of this article:

Vishal Dey1 Author Orcid Image ;   Peter Krasniak2 Author Orcid Image ;   Minh Nguyen2 Author Orcid Image ;   Clara Lee2 Author Orcid Image ;   Xia Ning1, 2, 3 Author Orcid Image
Article Authors Cited by (3) Tweetations (8) Metrics

Vishal Dey   1 , BSc ;   Peter Krasniak   2 , MD ;   Minh Nguyen   2 , MD ;   Clara Lee   2 , MD ;   Xia Ning   1, 2, 3 , PhD

1 Department of Computer Science and Engineering, The Ohio State University, Columbus, OH, United States

2 Department of Biomedical Informatics, The Ohio State University, Columbus, OH, United States

3 Translational Data Analytics Institute, The Ohio State University, Columbus, OH, United States

Corresponding Author:

  • Xia Ning, PhD
  • Department of Biomedical Informatics
  • The Ohio State University
  • 1800 Cannon Drive
  • Columbus, OH, 43210
  • United States
  • Phone: 1 6143662287
  • Email: ning.104@osu.edu