Optimizing prediction of response to antidepressant medications using machine learning and integrated genetic, clinical, and demographic data

Major depressive disorder (MDD) is complex and multifactorial, posing a major challenge of tailoring the optimal medication for each patient. Current practice for MDD treatment mainly relies on trial and error, with an estimated 42–53% response rates for antidepressant use. Here, we sought to genera...

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Detalles Bibliográficos
Autores principales: Taliaz, Dekel, Spinrad, Amit, Barzilay, Ran, Barnett-Itzhaki, Zohar, Averbuch, Dana, Teltsh, Omri, Schurr, Roy, Darki-Morag, Sne, Lerer, Bernard
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8266902/
https://www.ncbi.nlm.nih.gov/pubmed/34238923
http://dx.doi.org/10.1038/s41398-021-01488-3

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8266902/
https://www.ncbi.nlm.nih.gov/pubmed/34238923
http://dx.doi.org/10.1038/s41398-021-01488-3

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