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

Development and Evaluation of Research Methods, Instruments and Tools (494) Innovative Methods in Public Health and Surveillance (333) JMIR Theme Issue: COVID-19 Special Issue (2455) Natural Language Processing (697) Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (1047) Artificial Intelligence (1393) mHealth for Data Collection and Research (964) Dementia and Cognitive Decline (491) Infectious Diseases (non-STD/STI) (1580) Hygiene and Infection Prevention (323)

Published on in Vol 8 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/49562, first published .
Identifying X (Formerly Twitter) Posts Relevant to Dementia and COVID-19: Machine Learning Approach

Identifying X (Formerly Twitter) Posts Relevant to Dementia and COVID-19: Machine Learning Approach

Identifying X (Formerly Twitter) Posts Relevant to Dementia and COVID-19: Machine Learning Approach

Authors of this article:

Mehrnoosh Azizi1 Author Orcid Image ;   Ali Akbar Jamali1 Author Orcid Image ;   Raymond J Spiteri1 Author Orcid Image
Article Authors Cited by (1) Tweetations (3) Metrics

Journals

  1. Jamali A, Berger C, Spiteri R. Identification of depression predictors from standard health surveys using machine learning. Current Research in Behavioral Sciences 2024;7:100157 View