An efficient non-invasive model for predicting cognitive impairment based on comprehensive geriatric assessment: Machine learning and SHAP analysis.
- DOI
- 10.1177/25424823261415843
- Published
- 2026 Jan-Dec
- Container
- Journal of Alzheimer's disease reports
- 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.
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Cite this work
BibTeX
@article{allodium:10.1177/25424823261415843,
title = {An efficient non-invasive model for predicting cognitive impairment based on comprehensive geriatric assessment: Machine learning and SHAP analysis.},
author = {Zhang J and Li W and Wen S and Zhang X and Gao Y and Feng Y and Lü Y},
year = {2026},
journal = {Journal of Alzheimer's disease reports},
doi = {10.1177/25424823261415843},
url = {https://doi.org/10.1177/25424823261415843}
}RIS
TY - JOUR TI - An efficient non-invasive model for predicting cognitive impairment based on comprehensive geriatric assessment: Machine learning and SHAP analysis. AU - Zhang J AU - Li W AU - Wen S AU - Zhang X AU - Gao Y AU - Feng Y AU - Lü Y PY - 2026 JO - Journal of Alzheimer's disease reports DO - 10.1177/25424823261415843 UR - https://doi.org/10.1177/25424823261415843 ER -
APA
J, Z., W, L., S, W., X, Z., Y, G., Y, F., & Y, L. (2026). An efficient non-invasive model for predicting cognitive impairment based on comprehensive geriatric assessment: Machine learning and SHAP analysis.. Journal of Alzheimer's disease reports. https://doi.org/10.1177/25424823261415843
Source records
- pubmed · retrieved 2026-09-26T22:42:36.708Z