A machine learning approach to predicting clinical trajectories in bipolar disorder.
- DOI
- 10.1016/j.psychres.2026.117009
- Published
- 2026 May
- Container
- Psychiatry research
- Publisher
- Not recorded
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1016/j.psychres.2026.117009,
title = {A machine learning approach to predicting clinical trajectories in bipolar disorder.},
author = {Ejiohuo O and Adiukwu FN and Bamgboye AO and Folami S and Essien EA and Osagiede G and Olaleye OO},
year = {2026},
journal = {Psychiatry research},
doi = {10.1016/j.psychres.2026.117009},
url = {https://doi.org/10.1016/j.psychres.2026.117009}
}RIS
TY - JOUR TI - A machine learning approach to predicting clinical trajectories in bipolar disorder. AU - Ejiohuo O AU - Adiukwu FN AU - Bamgboye AO AU - Folami S AU - Essien EA AU - Osagiede G AU - Olaleye OO PY - 2026 JO - Psychiatry research DO - 10.1016/j.psychres.2026.117009 UR - https://doi.org/10.1016/j.psychres.2026.117009 ER -
APA
O, E., FN, A., AO, B., S, F., EA, E., G, O., & OO, O. (2026). A machine learning approach to predicting clinical trajectories in bipolar disorder.. Psychiatry research. https://doi.org/10.1016/j.psychres.2026.117009
Source records
- pubmed · retrieved 2026-09-26T17:36:27.970Z