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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...
| Autores principales: | , , , , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Nature Publishing Group UK
2021
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| Materias: | |
| 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 |