A risk identification model for detection of patients at risk of antidepressant discontinuation

PURPOSE: Between 30 and 68% of patients prematurely discontinue their antidepressant treatment, posing significant risks to patient safety and healthcare outcomes. Online healthcare forums have the potential to offer a rich and unique source of data, revealing dimensions of antidepressant discontinu...

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Detalles Bibliográficos
Autores principales: Zolnour, Ali, Eldredge, Christina E., Faiola, Anthony, Yaghoobzadeh, Yadollah, Khani, Masoud, Foy, Doreen, Topaz, Maxim, Kharrazi, Hadi, Fung, Kin Wah, Fontelo, Paul, Davoudi, Anahita, Tabaie, Azade, Breitinger, Scott A., Oesterle, Tyler S., Rouhizadeh, Masoud, Zonnor, Zahra, Moen, Hans, Patrick, Timothy B., Zolnoori, Maryam
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Artificial Intelligence
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10484003/
https://www.ncbi.nlm.nih.gov/pubmed/37693012
http://dx.doi.org/10.3389/frai.2023.1229609

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10484003/
https://www.ncbi.nlm.nih.gov/pubmed/37693012
http://dx.doi.org/10.3389/frai.2023.1229609

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