Week-ahead prediction of depressive episodes using wearable-derived circadian biomarkers: A multicenter deep learning study with risk-based operating thresholds.

Kim B, Chae M, Seo H, Jeong J, Park S, Jeong I, Kim Y, Kim Y, Jung T, Lee T, Cho CH, Yeom JW, Lee T, Lee HJ, Lee H

Open source

DOI
10.1016/j.jad.2026.122076
Published
2026 Nov 1
Container
Journal of affective disorders
Publisher
Not recorded
Open access
unknown

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BibTeX

@article{allodium:10.1016/j.jad.2026.122076,
  title = {Week-ahead prediction of depressive episodes using wearable-derived circadian biomarkers: A multicenter deep learning study with risk-based operating thresholds.},
  author = {Kim B and Chae M and Seo H and Jeong J and Park S and Jeong I and Kim Y and Kim Y and Jung T and Lee T and Cho CH and Yeom JW and Lee T and Lee HJ and Lee H},
  year = {2026},
  journal = {Journal of affective disorders},
  doi = {10.1016/j.jad.2026.122076},
  url = {https://doi.org/10.1016/j.jad.2026.122076}
}

RIS

TY  - JOUR
TI  - Week-ahead prediction of depressive episodes using wearable-derived circadian biomarkers: A multicenter deep learning study with risk-based operating thresholds.
AU  - Kim B
AU  - Chae M
AU  - Seo H
AU  - Jeong J
AU  - Park S
AU  - Jeong I
AU  - Kim Y
AU  - Kim Y
AU  - Jung T
AU  - Lee T
AU  - Cho CH
AU  - Yeom JW
AU  - Lee T
AU  - Lee HJ
AU  - Lee H
PY  - 2026
JO  - Journal of affective disorders
DO  - 10.1016/j.jad.2026.122076
UR  - https://doi.org/10.1016/j.jad.2026.122076
ER  - 

APA

B, K., M, C., H, S., J, J., S, P., I, J., Y, K., Y, K., T, J., T, L., CH, C., JW, Y., T, L., HJ, L., & H, L. (2026). Week-ahead prediction of depressive episodes using wearable-derived circadian biomarkers: A multicenter deep learning study with risk-based operating thresholds.. Journal of affective disorders. https://doi.org/10.1016/j.jad.2026.122076

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