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

JMH Theme Issue: COVID-19 and Mental Health: Impact and Interventions 2023 (409) JMIR Theme Issue: COVID-19 Special Issue (2553) Machine Learning (2074) Outbreak and Pandemic Preparedness and Management (1826) Theme Issue: Novel Coronavirus (COVID-19) Outbreak Rapid Reports (1542) Users' and Patients' Needs for Mental Health Services (502) Anxiety and Stress Disorders (1328) Infectious Diseases (non-STD/STI) (1725) Depression and Mood Disorders; Suicide Prevention (1689)

Published on in Vol 8, No 4 (2021): April

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/25097, first published .
Learning the Mental Health Impact of COVID-19 in the United States With Explainable Artificial Intelligence: Observational Study

Learning the Mental Health Impact of COVID-19 in the United States With Explainable Artificial Intelligence: Observational Study

Learning the Mental Health Impact of COVID-19 in the United States With Explainable Artificial Intelligence: Observational Study

Authors of this article:

Indra Prakash Jha1 Author Orcid Image ;   Raghav Awasthi1 Author Orcid Image ;   Ajit Kumar2 Author Orcid Image ;   Vibhor Kumar1 Author Orcid Image ;   Tavpritesh Sethi1 Author Orcid Image
Article Authors Cited by (39) Tweetations (6) Metrics

Journals

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  16. Han X, Hu N. Prediction of one- and three-months yoga practices effect on chronic venous insufficiency based on machine learning classifiers. Egyptian Informatics Journal 2024;27:100507 View
  17. Sun Y, Xu C, Xu H. Social identity in trusting artificial intelligence agents: Evidence from lab and online experiments. Managerial and Decision Economics 2024;45(8):5899 View
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