AI-assisted screening for mild cognitive impairment using routine EHR data: a Gradient Boosting approach
An ML model using routine outpatient EHR can discriminate MCI in older adults (AUC ≈ 0.85), supporting potential for automated, low-cost screening in primary care. Using the predicted probabilities generated in this analysis, we assessed calibration and conducted a decision-curve analysis. While the model shows good discrimination and calibration, external validation is still required to confirm clinical utility and refine operating thresholds.
Authors
- Tao Ye (ORCID: https://orcid.org/0009-0002-1089-6528)
- Jianghua Peng
Institutions
- Shaoxing University (CN)
- Shaoxing People's Hospital (CN)
Publication Details
- Journal
- Frontiers in Neurology
- Published
- 2026-02-17
- DOI
- https://doi.org/10.3389/fneur.2026.1718791
- Primary Topic
- Machine Learning in Healthcare
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Medical Science and Technology Project of Zhejiang Province
- Science and Technology Program of Zhejiang Province