Published on 27.04.18 in Vol 20, No 4 (2018): April
Works citing "Solution to Detect, Classify, and Report Illicit Online Marketing and Sales of Controlled Substances via Twitter: Using Machine Learning and Web Forensics to Combat Digital Opioid Access"
According to Crossref, the following articles are citing this article (DOI 10.2196/10029):
(note that this is only a small subset of citations)
- Miklosik A, Kuchta M, Evans N, Zak S. Towards the Adoption of Machine Learning-Based Analytical Tools in Digital Marketing. IEEE Access 2019;7:85705CrossRef
- Li J, Xu Q, Shah N, Mackey TK. A Machine Learning Approach for the Detection and Characterization of Illicit Drug Dealers on Instagram: Model Evaluation Study. Journal of Medical Internet Research 2019;21(6):e13803CrossRef
- Mackey TK. Opioids and the Internet: Convergence of Technology and Policy to Address the Illicit Online Sales of Opioids. Health Services Insights 2018;11:117863291880099CrossRef
- Fittler A, Vida RG, Káplár M, Botz L. Consumers Turning to the Internet Pharmacy Market: Cross-Sectional Study on the Frequency and Attitudes of Hungarian Patients Purchasing Medications Online. Journal of Medical Internet Research 2018;20(8):e11115CrossRef