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

New Methods (901) Medicine 2.0: Social Media, Open, Participatory, Collaborative Medicine (1552) Infodemiology and Infoveillance (1269) Smoking Cessation (514) Mass Media/Social Media Communication and Campaigns (446) Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (1010) Imaging Informatics (181) Water, Oceans, and Hydro Sciences (35)

Published on in Vol 20, No 11 (2018): November

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/10513, first published .
Automated Identification of Hookahs (Waterpipes) on Instagram: An Application in Feature Extraction Using Convolutional Neural Network and Support Vector Machine Classification

Automated Identification of Hookahs (Waterpipes) on Instagram: An Application in Feature Extraction Using Convolutional Neural Network and Support Vector Machine Classification

Automated Identification of Hookahs (Waterpipes) on Instagram: An Application in Feature Extraction Using Convolutional Neural Network and Support Vector Machine Classification

Authors of this article:

Youshan Zhang1 Author Orcid Image ;   Jon-Patrick Allem2 Author Orcid Image ;   Jennifer Beth Unger2 Author Orcid Image ;   Tess Boley Cruz2 Author Orcid Image
Article Authors Cited by (20) Tweetations (12) Metrics

Journals

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  2. Mavragani A. Infodemiology and Infoveillance: Scoping Review. Journal of Medical Internet Research 2020;22(4):e16206 View
  3. Tobore I, Li J, Yuhang L, Al-Handarish Y, Kandwal A, Nie Z, Wang L. Deep Learning Intervention for Health Care Challenges: Some Biomedical Domain Considerations. JMIR mHealth and uHealth 2019;7(8):e11966 View
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  5. Peine A, Hallawa A, Schöffski O, Dartmann G, Fazlic L, Schmeink A, Marx G, Martin L. A Deep Learning Approach for Managing Medical Consumable Materials in Intensive Care Units via Convolutional Neural Networks: Technical Proof-of-Concept Study. JMIR Medical Informatics 2019;7(4):e14806 View
  6. Baghdadi S, Aboutabit N. Transfer Learning for classifying front and rear views of vehicles. Journal of Physics: Conference Series 2021;1743(1):012007 View
  7. Singh T, Roberts K, Cohen T, Cobb N, Wang J, Fujimoto K, Myneni S. Social Media as a Research Tool (SMaaRT) for Risky Behavior Analytics: Methodological Review. JMIR Public Health and Surveillance 2020;6(4):e21660 View
  8. Lv H, Yang X, Wang B, Wang S, Du X, Tan Q, Hao Z, Liu Y, Yan J, Xia Y. Machine Learning–Driven Models to Predict Prognostic Outcomes in Patients Hospitalized With Heart Failure Using Electronic Health Records: Retrospective Study. Journal of Medical Internet Research 2021;23(4):e24996 View
  9. Malik A, Berggren W, Al-Busaidi A. Instagram as a research tool for examining tobacco-related content: A methodological review. Technology in Society 2022;70:102008 View
  10. Singh T, Roberts K, Cohen T, Cobb N, Franklin A, Myneni S. Discerning conversational context in online health communities for personalized digital behavior change solutions using Pragmatics to Reveal Intent in Social Media (PRISM) framework. Journal of Biomedical Informatics 2023;140:104324 View
  11. Nanni L, Ghidoni S, Brahnam S. Deep Features for Training Support Vector Machines. Journal of Imaging 2021;7(9):177 View
  12. Wang S, Du X, Liu G, Xing H, Jiao Z, Yan J, Liu Y, Lv H, Xia Y. An Interpretable Data-Driven Medical Knowledge Discovery Pipeline Based on Artificial Intelligence. IEEE Journal of Biomedical and Health Informatics 2023;27(10):5099 View

Books/Policy Documents

  1. Wu Y, Zhang Y. Intelligent Systems and Applications. View
  2. Zhang Y, Davison B. Pattern Recognition. ICPR International Workshops and Challenges. View