Building an auxiliary diagnostic and treatment efficacy prediction model for adolescent depression using machine learning based on electroencephalography technology.
- DOI
- 10.3389/fnhum.2026.1774822
- Published
- 2026
- Container
- Frontiers in human neuroscience
- Publisher
- Not recorded
- Open access
- yes
Credibility signals
limited evidence Score 45/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.
Show all credibility signals
- cautionDOI registered: No matching Crossref record was present in this response.
- cautionDOI resolves: No matching Crossref record was present in this response.
- not scoredDirectory of Open Access Journals: No matching DOAJ record was present in this response. No allow-list match; this is not evidence of low credibility.
- not scoredMEDLINE indexed: Not checked or no result supplied; no credibility inference made.
- not scoredOpenAlex core source: Not checked or no result supplied; no credibility inference made.
- not scoredKnown publisher allow-list: Not checked or no result supplied; no credibility inference made.
- not scoredROR affiliation: Not checked or no result supplied; no credibility inference made.
- not scoredRetraction Watch retraction: No retraction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete.
- not scoredRetraction Watch expression of concern: No expression of concern notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete.
- not scoredRetraction Watch correction: No correction notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete.
- not scoredRetraction Watch reinstatement: No reinstatement notice matched this DOI in the deployed snapshot. No matching event found; coverage may be incomplete.
- supportingOpen access status: Normalized open-access status: open.
- not scoredPublication license: Not checked or no result supplied; no credibility inference made.
- not scoredPublication version: A publication version was supplied but is not scored.
- cautionMetadata completeness: 5 of 6 scored descriptive metadata groups are present; missing fields increase uncertainty.
Cite this work
BibTeX
@article{allodium:10.3389/fnhum.2026.1774822,
title = {Building an auxiliary diagnostic and treatment efficacy prediction model for adolescent depression using machine learning based on electroencephalography technology.},
author = {Peng T and Chi A and Yang J and Ren Y and Li Y and Fan J},
year = {2026},
journal = {Frontiers in human neuroscience},
doi = {10.3389/fnhum.2026.1774822},
url = {https://doi.org/10.3389/fnhum.2026.1774822}
}RIS
TY - JOUR TI - Building an auxiliary diagnostic and treatment efficacy prediction model for adolescent depression using machine learning based on electroencephalography technology. AU - Peng T AU - Chi A AU - Yang J AU - Ren Y AU - Li Y AU - Fan J PY - 2026 JO - Frontiers in human neuroscience DO - 10.3389/fnhum.2026.1774822 UR - https://doi.org/10.3389/fnhum.2026.1774822 ER -
APA
T, P., A, C., J, Y., Y, R., Y, L., & J, F. (2026). Building an auxiliary diagnostic and treatment efficacy prediction model for adolescent depression using machine learning based on electroencephalography technology.. Frontiers in human neuroscience. https://doi.org/10.3389/fnhum.2026.1774822
Source records
- pubmed · retrieved 2026-09-27T15:56:29.248Z