Published on in Vol 10, No 7 (2022): July

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/37201, first published .
Extraction of Explicit and Implicit Cause-Effect Relationships in Patient-Reported Diabetes-Related Tweets From 2017 to 2021: Deep Learning Approach

Extraction of Explicit and Implicit Cause-Effect Relationships in Patient-Reported Diabetes-Related Tweets From 2017 to 2021: Deep Learning Approach

Extraction of Explicit and Implicit Cause-Effect Relationships in Patient-Reported Diabetes-Related Tweets From 2017 to 2021: Deep Learning Approach

Journals

  1. Kabir M, Phillips T, Luo X, Al Hasan M. ASPER: Attention-based approach to extract syntactic patterns denoting semantic relations in sentential context. Natural Language Processing Journal 2023;3:100011 View
  2. Zibaei E, Borth R. Building causal models for finding actual causes of unmanned aerial vehicle failures. Frontiers in Robotics and AI 2024;11 View
  3. Yang T, Sucholutsky I, Jen K, Schonlau M. exKidneyBERT: a language model for kidney transplant pathology reports and the crucial role of extended vocabularies. PeerJ Computer Science 2024;10:e1888 View
  4. Wessel D, Pogrebnyakov N. Using Social Media as a Source of Real-World Data for Pharmaceutical Drug Development and Regulatory Decision Making. Drug Safety 2024;47(5):495 View