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

Machine Learning (1121) Data Science (150) Natural Language Processing (535) Infodemiology and Infoveillance (1127) Mass Media/Social Media Communication and Campaigns (406)

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 Ahne 1, 2 Author Orcid Image ;   Vivek Khetan 3 Author Orcid Image ;   Xavier Tannier 4 Author Orcid Image ;   Md Imbesat Hassan Rizvi 5 Author Orcid Image ;   Thomas Czernichow 2 Author Orcid Image ;   Francisco Orchard 2 Author Orcid Image ;   Charline Bour 6 Author Orcid Image ;   Andrew Fano 3 ;   Guy Fagherazzi 6 Author Orcid Image
Article Authors Cited by (1) 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 2023:100011 View