Evaluation of a Machine Learning Model Based on Pretreatment Symptoms and Electroencephalographic Features to Predict Outcomes of Antidepressant Treatment in Adults With Depression: A Prespecified Secondary Analysis of a Randomized Clinical Trial.
- DOI
- 10.1001/jamanetworkopen.2020.6653
- Published
- 2020 Jun 1
- Container
- JAMA network open
- Publisher
- Not recorded
- Open access
- yes
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Cite this work
BibTeX
@article{allodium:10.1001/jamanetworkopen.2020.6653,
title = {Evaluation of a Machine Learning Model Based on Pretreatment Symptoms and Electroencephalographic Features to Predict Outcomes of Antidepressant Treatment in Adults With Depression: A Prespecified Secondary Analysis of a Randomized Clinical Trial.},
author = {Rajpurkar P and Yang J and Dass N and Vale V and Keller AS and Irvin J and Taylor Z and Basu S and Ng A and Williams LM},
year = {2020},
journal = {JAMA network open},
doi = {10.1001/jamanetworkopen.2020.6653},
url = {https://doi.org/10.1001/jamanetworkopen.2020.6653}
}RIS
TY - JOUR TI - Evaluation of a Machine Learning Model Based on Pretreatment Symptoms and Electroencephalographic Features to Predict Outcomes of Antidepressant Treatment in Adults With Depression: A Prespecified Secondary Analysis of a Randomized Clinical Trial. AU - Rajpurkar P AU - Yang J AU - Dass N AU - Vale V AU - Keller AS AU - Irvin J AU - Taylor Z AU - Basu S AU - Ng A AU - Williams LM PY - 2020 JO - JAMA network open DO - 10.1001/jamanetworkopen.2020.6653 UR - https://doi.org/10.1001/jamanetworkopen.2020.6653 ER -
APA
P, R., J, Y., N, D., V, V., AS, K., J, I., Z, T., S, B., A, N., & LM, W. (2020). Evaluation of a Machine Learning Model Based on Pretreatment Symptoms and Electroencephalographic Features to Predict Outcomes of Antidepressant Treatment in Adults With Depression: A Prespecified Secondary Analysis of a Randomized Clinical Trial.. JAMA network open. https://doi.org/10.1001/jamanetworkopen.2020.6653
Source records
- pubmed · retrieved 2026-09-25T11:17:56.310Z