Published on in Vol 6, No 5 (2022): May

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/36238, first published .
Global User-Level Perception of COVID-19 Contact Tracing Applications: Data-Driven Approach Using Natural Language Processing

Global User-Level Perception of COVID-19 Contact Tracing Applications: Data-Driven Approach Using Natural Language Processing

Global User-Level Perception of COVID-19 Contact Tracing Applications: Data-Driven Approach Using Natural Language Processing

Journals

  1. Zou K, Li J. Enhanced Patient-Centricity: How the Biopharmaceutical Industry Is Optimizing Patient Care through AI/ML/DL. Healthcare 2022;10(10):1997 View
  2. Hang C, Tsai Y, Yu P, Chen J, Tan C. Privacy-Enhancing Digital Contact Tracing with Machine Learning for Pandemic Response: A Comprehensive Review. Big Data and Cognitive Computing 2023;7(2):108 View
  3. Zheng C, Li W, Wang S, Ye H, Xu K, Fang W, Dong Y, Wang Z, Qiao T. Automated detection of steps in videos of strabismus surgery using deep learning. BMC Ophthalmology 2024;24(1) View
  4. Ayub M, Zamir M, Khan I, Naseem H, Ahmad N, Ahmad K. Social Media and Artificial Intelligence for Sustainable Cities and Societies: A Water Quality Analysis Use-Case. Computing&AI Connect 2024;1(1):1 View

Conference Proceedings

  1. Zamir M, Ayub M, Khan J, Ikram M, Ahmad N, Ahmad K. 2023 1st International Conference on Advanced Innovations in Smart Cities (ICAISC). Document Provenance and Authentication through Authorship Classification View