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

Theme Issue: Novel Coronavirus (COVID-19) Outbreak Rapid Reports (1517) Data Science (270) Infodemiology and Infoveillance (1349) Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (1041) JMIR Theme Issue: COVID-19 Special Issue (2452)

Published on in Vol 6, No 2 (2020): Apr-Jun

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/18828, first published .
Predicting COVID-19 Incidence Through Analysis of Google Trends Data in Iran: Data Mining and Deep Learning Pilot Study

Predicting COVID-19 Incidence Through Analysis of Google Trends Data in Iran: Data Mining and Deep Learning Pilot Study

Predicting COVID-19 Incidence Through Analysis of Google Trends Data in Iran: Data Mining and Deep Learning Pilot Study

Authors of this article:

Seyed Mohammad Ayyoubzadeh1 Author Orcid Image ;   Seyed Mehdi Ayyoubzadeh2 Author Orcid Image ;   Hoda Zahedi3 Author Orcid Image ;   Mahnaz Ahmadi4 Author Orcid Image ;   Sharareh R Niakan Kalhori1 Author Orcid Image
Article Authors Cited by (249) Tweetations (5) Metrics

Seyed Mohammad Ayyoubzadeh   1 , MSc ;   Seyed Mehdi Ayyoubzadeh   2 , BSc ;   Hoda Zahedi   3 , BSc ;   Mahnaz Ahmadi   4 , MSc ;   Sharareh R Niakan Kalhori   1 , PhD

1 Department of Health Information Management, School of Allied Medical Sciences, Tehran University of Medical Sciences, Tehran, Iran

2 Department of Electrical and Computer Engineering, McMaster University, Hamilton, ON, Canada

3 School of Health Management and Information Sciences, Iran University of Medical Sciences, Tehran, Iran

4 Department of Pharmaceutics, School of Pharmacy, Shahid Beheshti University of Medical Sciences, Tehran, Iran

Corresponding Author:

  • Sharareh R Niakan Kalhori, PhD
  • Department of Health Information Management
  • School of Allied Medical Sciences
  • Tehran University of Medical Sciences
  • 3rd Floor, No 17
  • Farredanesh Alley, Ghods St, Enghelab Ave
  • Tehran
  • Iran
  • Phone: 98 21-88983025
  • Fax: 98 21-88983037
  • Email: niakan2@gmail.com