A Smartphone-Based Acoustic Machine Learning Pipeline for Detecting Suicidal Ideation: Case-Control Model Development and Validation Study.
- DOI
- 10.2196/92646
- Published
- 2026 Sep 15
- Container
- JMIR formative research
- 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:10.2196/92646,
title = {A Smartphone-Based Acoustic Machine Learning Pipeline for Detecting Suicidal Ideation: Case-Control Model Development and Validation Study.},
author = {Lyu M and Tan L and Xiao J and Huang H and Liu F and Qi J and Huang T and Lei J and Zhao Z and Jiang T and Liu Z and Wang X and Zhong J and Feng Z},
year = {2026},
journal = {JMIR formative research},
doi = {10.2196/92646},
url = {https://doi.org/10.2196/92646}
}RIS
TY - JOUR TI - A Smartphone-Based Acoustic Machine Learning Pipeline for Detecting Suicidal Ideation: Case-Control Model Development and Validation Study. AU - Lyu M AU - Tan L AU - Xiao J AU - Huang H AU - Liu F AU - Qi J AU - Huang T AU - Lei J AU - Zhao Z AU - Jiang T AU - Liu Z AU - Wang X AU - Zhong J AU - Feng Z PY - 2026 JO - JMIR formative research DO - 10.2196/92646 UR - https://doi.org/10.2196/92646 ER -
APA
M, L., L, T., J, X., H, H., F, L., J, Q., T, H., J, L., Z, Z., T, J., Z, L., X, W., J, Z., & Z, F. (2026). A Smartphone-Based Acoustic Machine Learning Pipeline for Detecting Suicidal Ideation: Case-Control Model Development and Validation Study.. JMIR formative research. https://doi.org/10.2196/92646
Source records
- pubmed · retrieved 2026-09-25T05:10:42.384Z