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

Early Results in Infodemiology and Infoveillance (77) Infodemiology and Infoveillance (1369) Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (1050) Machine Learning (1501)

Published on in Vol 6, No 6 (2022): June

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/34834, first published .
Pretrained Transformer Language Models Versus Pretrained Word Embeddings for the Detection of Accurate Health Information on Arabic Social Media: Comparative Study

Pretrained Transformer Language Models Versus Pretrained Word Embeddings for the Detection of Accurate Health Information on Arabic Social Media: Comparative Study

Pretrained Transformer Language Models Versus Pretrained Word Embeddings for the Detection of Accurate Health Information on Arabic Social Media: Comparative Study

Authors of this article:

Yahya Albalawi1, 2, 3 Author Orcid Image ;   Nikola S Nikolov1 Author Orcid Image ;   Jim Buckley1, 3 Author Orcid Image
Article Authors Cited by (3) Tweetations (7) Metrics

Journals

  1. Boulesnane A, Meshoul S, Aouissi K. Influenza-like Illness Detection from Arabic Facebook Posts Based on Sentiment Analysis and 1D Convolutional Neural Network. Mathematics 2022;10(21):4089 View
  2. Bagla P, Kumar K. Breaking down health fakes: a hybrid DNN model for multi-class classification on a self-constructed dataset. Sādhanā 2023;48(4) View
  3. Cho H, Jun T, Kim Y, Kang H, Ahn I, Gwon H, Kim Y, Seo J, Choi H, Kim M, Han J, Kee G, Park S, Ko S. Task-Specific Transformer-Based Language Models in Health Care: Scoping Review. JMIR Medical Informatics 2024;12:e49724 View