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

Machine Learning (1465) Data Science (270) Natural Language Processing (692) Infodemiology and Infoveillance (1349) Mass Media/Social Media Communication and Campaigns (461)

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

Authors of this article:

Adrian Ahne1, 2 Author Orcid Image ;   Vivek Khetan3 Author Orcid Image ;   Xavier Tannier4 Author Orcid Image ;   Md Imbesat Hassan Rizvi5 Author Orcid Image ;   Thomas Czernichow2 Author Orcid Image ;   Francisco Orchard2 Author Orcid Image ;   Charline Bour6 Author Orcid Image ;   Andrew Fano3 ;   Guy Fagherazzi6 Author Orcid Image
Article Authors Cited by (7) Tweetations (8) Metrics

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
  5. Nerella S, Bandyopadhyay S, Zhang J, Contreras M, Siegel S, Bumin A, Silva B, Sena J, Shickel B, Bihorac A, Khezeli K, Rashidi P. Transformers and large language models in healthcare: A review. Artificial Intelligence in Medicine 2024;154:102900 View
  6. Trevena W, Zhong X, Alvarado M, Semenov A, Oktay A, Devlin D, Gohil A, Chittimouju S. Utilizing Large Language Models to Detect and Understand Drug Discontinuation Events in Online Forums: Development and Validation Study (Preprint). Journal of Medical Internet Research 2023 View