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

Infodemiology and Infoveillance (1350) Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (1042) Machine Learning (1473) Natural Language Processing (693) Medicine 2.0: Social Media, Open, Participatory, Collaborative Medicine (1644) Artificial Intelligence (1379)

Published on in Vol 25 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/47014, first published .
Identifying Potential Lyme Disease Cases Using Self-Reported Worldwide Tweets: Deep Learning Modeling Approach Enhanced With Sentimental Words Through Emojis

Identifying Potential Lyme Disease Cases Using Self-Reported Worldwide Tweets: Deep Learning Modeling Approach Enhanced With Sentimental Words Through Emojis

Identifying Potential Lyme Disease Cases Using Self-Reported Worldwide Tweets: Deep Learning Modeling Approach Enhanced With Sentimental Words Through Emojis

Authors of this article:

Elda Kokoe Elolo Laison1 Author Orcid Image ;   Mohamed Hamza Ibrahim2 Author Orcid Image ;   Srikanth Boligarla3 Author Orcid Image ;   Jiaxin Li3 Author Orcid Image ;   Raja Mahadevan3 Author Orcid Image ;   Austen Ng3 Author Orcid Image ;   Venkataraman Muthuramalingam3 Author Orcid Image ;   Wee Yi Lee3 Author Orcid Image ;   Yijun Yin3 Author Orcid Image ;   Bouchra R Nasri1 Author Orcid Image
Article Authors Cited by (1) Tweetations (2) Metrics

Elda Kokoe Elolo Laison   1 , MSc, MD ;   Mohamed Hamza Ibrahim   2 , PhD ;   Srikanth Boligarla   3 , ALM ;   Jiaxin Li   3 , ALM ;   Raja Mahadevan   3 , ALM ;   Austen Ng   3 , ALM ;   Venkataraman Muthuramalingam   3 , ALM ;   Wee Yi Lee   3 , ALM ;   Yijun Yin   3 , ALM ;   Bouchra R Nasri   1 , PhD

1 Département de médecine sociale et préventive, École de Santé Publique de l’Université de Montréal, Université de Montréal, Montréal, QC, Canada

2 Department of Mathematics, Faculty of Science, Zagazig University, Zagazig, Egypt

3 Harvard Extension School, Harvard University, Cambridge, MA, United States

Corresponding Author:

  • Bouchra R Nasri, PhD
  • Département de médecine sociale et préventive
  • École de Santé Publique de l’Université de Montréal
  • Université de Montréal
  • 7101 Park Ave
  • Montréal, QC, H3N 1X9
  • Canada
  • Phone: 1 514 343-7973
  • Email: bouchra.nasri@umontreal.ca