Interpretable machine learning for classification and risk factor identification of anxiety, depression, and insomnia symptoms after the full opening of China's COVID-19 lockdown.

Li Z, Li J, Zhang A, Liu P, Su G, Wang Z, Zhang Y, Wang Y, Wu H, Ma Y, Ge J, Liu M.

Open source

DOI: 10.1186/s12888-025-07569-7
Published: 2025-11-14
Container: BMC Psychiatry
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.1186/s12888-025-07569-7,
  title = {Interpretable machine learning for classification and risk factor identification of anxiety, depression, and insomnia symptoms after the full opening of China's COVID-19 lockdown.},
  author = {Li Z and  Li J and  Zhang A and  Liu P and  Su G and  Wang Z and  Zhang Y and  Wang Y and  Wu H and  Ma Y and  Ge J and  Liu M.},
  year = {2025},
  journal = {BMC Psychiatry},
  doi = {10.1186/s12888-025-07569-7},
  url = {https://doi.org/10.1186/s12888-025-07569-7}
}

RIS

TY  - JOUR
TI  - Interpretable machine learning for classification and risk factor identification of anxiety, depression, and insomnia symptoms after the full opening of China's COVID-19 lockdown.
AU  - Li Z
AU  -  Li J
AU  -  Zhang A
AU  -  Liu P
AU  -  Su G
AU  -  Wang Z
AU  -  Zhang Y
AU  -  Wang Y
AU  -  Wu H
AU  -  Ma Y
AU  -  Ge J
AU  -  Liu M.
PY  - 2025
JO  - BMC Psychiatry
DO  - 10.1186/s12888-025-07569-7
UR  - https://doi.org/10.1186/s12888-025-07569-7
ER  -

APA

Z, L., J, L., A, Z., P, L., G, S., Z, W., Y, Z., Y, W., H, W., Y, M., J, G., & M., L. (2025). Interpretable machine learning for classification and risk factor identification of anxiety, depression, and insomnia symptoms after the full opening of China's COVID-19 lockdown.. BMC Psychiatry. https://doi.org/10.1186/s12888-025-07569-7

Source records

europe-pmc · retrieved 2026-09-27T02:34:53.050Z
doaj · retrieved 2026-09-27T02:34:53.061Z