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

Artificial Intelligence (2162) Smoking Cessation (633) Public (e)Health, Digital Epidemiology and Public Health Informatics (1022) Machine Learning (2095) Prevention and Health Promotion (1385) Innovative Methods in Public Health and Surveillance (388) Electronic/Mobile Data Capture, Internet-based Survey & Research Methodology (1001)

Published on in Vol 23, No 8 (2021): August

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/24408, first published .
Image Processing for Public Health Surveillance of Tobacco Point-of-Sale Advertising: Machine Learning–Based Methodology

Image Processing for Public Health Surveillance of Tobacco Point-of-Sale Advertising: Machine Learning–Based Methodology

Image Processing for Public Health Surveillance of Tobacco Point-of-Sale Advertising: Machine Learning–Based Methodology

Authors of this article:

Ned English1 Author Orcid Image ;   Andrew Anesetti-Rothermel2 Author Orcid Image ;   Chang Zhao1 Author Orcid Image ;   Andrew Latterner1 Author Orcid Image ;   Adam F Benson3 Author Orcid Image ;   Peter Herman1 Author Orcid Image ;   Sherry Emery1 Author Orcid Image ;   Jordan Schneider3 Author Orcid Image ;   Shyanika W Rose4 Author Orcid Image ;   Minal Patel3 Author Orcid Image ;   Barbara A Schillo3 Author Orcid Image
Article Authors Cited by (8) Tweetations (8) Metrics

Journals

  1. Ramezani M, Takian A, Bakhtiari A, Rabiee H, Ghazanfari S, Mostafavi H. The application of artificial intelligence in health policy: a scoping review. BMC Health Services Research 2023;23(1) View
  2. Murthy D, Ouellette R, Anand T, Radhakrishnan S, Mohan N, Lee J, Kong G. Using Computer Vision to Detect E-cigarette Content in TikTok Videos. Nicotine and Tobacco Research 2024;26(Supplement_1):S36 View
  3. Huguet N, Chen J, Parikh R, Marino M, Flocke S, Likumahuwa-Ackman S, Bekelman J, DeVoe J. Applying Machine Learning Techniques to Implementation Science. Online Journal of Public Health Informatics 2024;16:e50201 View
  4. Alqahtani M, Alanazi A, Algarni S, Aljohani H, Alenezi F, F Alotaibi T, Alotaibi M, K Alqahtani M, Alahmari M, S Alwadeai K, M Alghamdi S, Almeshari M, Alshammari T, Mumenah N, Al Harbi E, Al Nufaiei Z, Alhuthail E, Alzahrani E, Alahmadi H, Alarifi A, Zaidan A, T Ismaeil T. Unveiling the Influence of AI on Advancements in Respiratory Care: Narrative Review. Interactive Journal of Medical Research 2024;13:e57271 View
  5. Pitts S, Trigger S, Kelley D, Ahmed S. Detecting changes in tobacco product marketplace prominence using social media, advertising, sales, and web traffic data: The example of Puff Bar in the United States tobacco marketplace from 2019 to 2021. PLOS ONE 2024;19(12):e0311723 View
  6. Olawade D, Aienobe-Asekharen C. Artificial intelligence in tobacco control: A systematic scoping review of applications, challenges, and ethical implications. International Journal of Medical Informatics 2025;202:105987 View
  7. Sayyad F, Shallari I, Mousavirad S, O’Nils M, Qureshi F. AdVision: An efficient and effective deep learning based advertisement detector for printed media. Machine Learning with Applications 2025;21:100686 View

Books/Policy Documents

  1. Zakaryapour Sayyad F, Shallari I, Mousavirad S, O’Nils M. Advances in Computing and Data Sciences. View