A hybrid SMOTE and Gaussian mixture model based optimized XGBoost framework for bipolar disorder detection.
- DOI
- 10.1038/s41598-026-39104-3
- Published
- 2026 Mar 3
- Container
- Scientific reports
- Publisher
- Not recorded
- Open access
- yes
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Cite this work
BibTeX
@article{allodium:10.1038/s41598-026-39104-3,
title = {A hybrid SMOTE and Gaussian mixture model based optimized XGBoost framework for bipolar disorder detection.},
author = {Kumar S and Kumari D and Panwar A and Sagar S and Herout L and Namazi H and Bhati NS},
year = {2026},
journal = {Scientific reports},
doi = {10.1038/s41598-026-39104-3},
url = {https://doi.org/10.1038/s41598-026-39104-3}
}RIS
TY - JOUR TI - A hybrid SMOTE and Gaussian mixture model based optimized XGBoost framework for bipolar disorder detection. AU - Kumar S AU - Kumari D AU - Panwar A AU - Sagar S AU - Herout L AU - Namazi H AU - Bhati NS PY - 2026 JO - Scientific reports DO - 10.1038/s41598-026-39104-3 UR - https://doi.org/10.1038/s41598-026-39104-3 ER -
APA
S, K., D, K., A, P., S, S., L, H., H, N., & NS, B. (2026). A hybrid SMOTE and Gaussian mixture model based optimized XGBoost framework for bipolar disorder detection.. Scientific reports. https://doi.org/10.1038/s41598-026-39104-3
Source records
- pubmed · retrieved 2026-09-26T22:48:00.600Z