Interpretable Feature Selection and Hybrid Deep Learning Models for Depressive Symptoms Prediction from Wearable Device Data.
- DOI
- 10.1007/s10916-026-02354-9
- Published
- 2026 Mar 3
- Container
- Journal of medical systems
- Publisher
- Not recorded
- Open access
- yes
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Cite this work
BibTeX
@article{allodium:10.1007/s10916-026-02354-9,
title = {Interpretable Feature Selection and Hybrid Deep Learning Models for Depressive Symptoms Prediction from Wearable Device Data.},
author = {Ko J and Oh S and Enkhbayar D and Lee JK and Chung MK and Shin T and Kim MH and Lim HS and Urtnasan E and Key J},
year = {2026},
journal = {Journal of medical systems},
doi = {10.1007/s10916-026-02354-9},
url = {https://doi.org/10.1007/s10916-026-02354-9}
}RIS
TY - JOUR TI - Interpretable Feature Selection and Hybrid Deep Learning Models for Depressive Symptoms Prediction from Wearable Device Data. AU - Ko J AU - Oh S AU - Enkhbayar D AU - Lee JK AU - Chung MK AU - Shin T AU - Kim MH AU - Lim HS AU - Urtnasan E AU - Key J PY - 2026 JO - Journal of medical systems DO - 10.1007/s10916-026-02354-9 UR - https://doi.org/10.1007/s10916-026-02354-9 ER -
APA
J, K., S, O., D, E., JK, L., MK, C., T, S., MH, K., HS, L., E, U., & J, K. (2026). Interpretable Feature Selection and Hybrid Deep Learning Models for Depressive Symptoms Prediction from Wearable Device Data.. Journal of medical systems. https://doi.org/10.1007/s10916-026-02354-9
Source records
- pubmed · retrieved 2026-09-26T14:57:20.352Z