Early Detection of Mental Health Crises through Artificial-Intelligence-Powered Social Media Analysis: A Prospective Observational Study

AI-powered analysis of social media data shows promise for the early detection of mental health crises across diverse linguistic and cultural contexts. However, ethical challenges, including privacy concerns, potential stigmatization, and cultural biases, need careful consideration. Future research should focus on longitudinal outcome studies, ethical integration of the method with existing mental health services, and developing personalized, culturally sensitive models.

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Publication Details

Journal
Journal of Personalized Medicine
Published
2024-09-09
DOI
https://doi.org/10.3390/jpm14090958
Citations
25
Primary Topic
Mental Health via Writing
Type
article
Field-Weighted Citation Impact
16.09
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article

Early Detection of Mental Health Crises through Artificial-Intelligence-Powered Social Media Analysis: A Prospective Observational Study

Masab Mansoor, Kashif Ansari
25 citations
Journal of Personalized Medicine
Mental Health via Writing
16.09
article

Early Detection of Mental Health Crises through Artificial-Intelligence-Powered Social Media Analysis: A Prospective Observational Study

Masab Mansoor, Kashif Ansari
article en
25 citations

Abstract

AI-powered analysis of social media data shows promise for the early detection of mental health crises across diverse linguistic and cultural contexts. However, ethical challenges, including privacy concerns, potential stigmatization, and cultural biases, need careful consideration. Future research should focus on longitudinal outcome studies, ethical integration of the method with existing mental health services, and developing personalized, culturally sensitive models.

Journal of Personalized MedicineVol. 14(9)
Houston Medical Center (US), Edward Via College of Osteopathic Medicine (US)
Quality Education
Openalex Percentile: Top 1%
Mental Health via Writing
16.09
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