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

Discretionary Corrigenda (87)

Published on in Vol 25 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/47549, first published .
Correction: Emotional Distress During COVID-19 by Mental Health Conditions and Economic Vulnerability: Retrospective Analysis of Survey-Linked Twitter Data With a Semisupervised Machine Learning Algorithm

Correction: Emotional Distress During COVID-19 by Mental Health Conditions and Economic Vulnerability: Retrospective Analysis of Survey-Linked Twitter Data With a Semisupervised Machine Learning Algorithm

Correction: Emotional Distress During COVID-19 by Mental Health Conditions and Economic Vulnerability: Retrospective Analysis of Survey-Linked Twitter Data With a Semisupervised Machine Learning Algorithm

Authors of this article:

Michiko Ueda1, 2 Author Orcid Image ;   Kohei Watanabe3 Author Orcid Image ;   Hajime Sueki4 Author Orcid Image
Article Authors Cited by (1) Tweetations (2) Metrics

Journals

  1. Torres A, Wenke M, Lieneck C, Ramamonjiarivelo Z, Ari A. A Systematic Review of Artificial Intelligence Used to Predict Loneliness, Social Isolation, and Drug Use During the COVID-19 Pandemic. Journal of Multidisciplinary Healthcare 2024;Volume 17:3403 View