Published on in Vol 4, No 1 (2020): January

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/13296, first published .
Using Natural Language Processing to Examine the Uptake, Content, and Readability of Media Coverage of a Pan-Canadian Drug Safety Research Project: Cross-Sectional Observational Study

Using Natural Language Processing to Examine the Uptake, Content, and Readability of Media Coverage of a Pan-Canadian Drug Safety Research Project: Cross-Sectional Observational Study

Using Natural Language Processing to Examine the Uptake, Content, and Readability of Media Coverage of a Pan-Canadian Drug Safety Research Project: Cross-Sectional Observational Study

Journals

  1. Abdalla M, Chen B, Santiago R, Young J, Eder L, Chan A, Pope E, Tu K, Jaakkimainen L, Drucker A. Accuracy of Algorithms to Identify People with Atopic Dermatitis in Ontario Routinely Collected Health Databases. Journal of Investigative Dermatology 2021;141(7):1840 View
  2. Shakeri Hossein Abad Z, Butler G, Thompson W, Lee J. Physical Activity, Sedentary Behavior, and Sleep on Twitter: Multicountry and Fully Labeled Public Data Set for Digital Public Health Surveillance Research. JMIR Public Health and Surveillance 2022;8(2):e32355 View