Influence of Functional Magnetic Resonance Imaging Data Preprocessing Pipelines on the Accuracy of Schizophrenia Classification Using Machine Learning Methods.
- DOI
- 10.17691/stm2026.18.3.02
- Published
- 2026
- Container
- Sovremennye tekhnologii v meditsine
- 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:10.17691/stm2026.18.3.02,
title = {Influence of Functional Magnetic Resonance Imaging Data Preprocessing Pipelines on the Accuracy of Schizophrenia Classification Using Machine Learning Methods.},
author = {Poyda AA and Orlov VA and Zhemchuzhnikov AD and Kozlov SO and Kartashov SI and Bravve LV and Kaydan MA and Kostyuk GP},
year = {2026},
journal = {Sovremennye tekhnologii v meditsine},
doi = {10.17691/stm2026.18.3.02},
url = {https://doi.org/10.17691/stm2026.18.3.02}
}RIS
TY - JOUR TI - Influence of Functional Magnetic Resonance Imaging Data Preprocessing Pipelines on the Accuracy of Schizophrenia Classification Using Machine Learning Methods. AU - Poyda AA AU - Orlov VA AU - Zhemchuzhnikov AD AU - Kozlov SO AU - Kartashov SI AU - Bravve LV AU - Kaydan MA AU - Kostyuk GP PY - 2026 JO - Sovremennye tekhnologii v meditsine DO - 10.17691/stm2026.18.3.02 UR - https://doi.org/10.17691/stm2026.18.3.02 ER -
APA
AA, P., VA, O., AD, Z., SO, K., SI, K., LV, B., MA, K., & GP, K. (2026). Influence of Functional Magnetic Resonance Imaging Data Preprocessing Pipelines on the Accuracy of Schizophrenia Classification Using Machine Learning Methods.. Sovremennye tekhnologii v meditsine. https://doi.org/10.17691/stm2026.18.3.02
Source records
- pubmed · retrieved 2026-09-25T06:28:04.675Z
- europe-pmc · retrieved 2026-09-25T06:28:04.659Z