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An Ensemble Learning Artificial Intelligence Model for Alzheimer's Disease Detection Using OCT
An Ran Ran, Xiaoyan Hu, Herbert Y.H. Hui, Jiajia Dai, Victor T.T. Chan, Ko Ho, Lisa WC Au, Chak Fung Ng et al.. Ophthalmology Science, 2026-01-10
Topic: Amyloid, tau and blood-test diagnosis
For detecting AD-dementia, the ensemble model achieved the area under the receiver operating characteristic curve (AUROC) of 0.943 (95% confidence interval, 0.906-0.980), 0.786 (95% confidence interval, 0.673-0.899), and 0.795 (95% confidence interval, 0.716-0.874) in the internal validation, External-1, and External-2, respectively. For detecting AD-MCI defined by PET biomarkers, the ensemble model achieved AUROCs of 0.787 (95% confidence interval, 0.643-0.931) and 0.791 (95% confidence interval, 0.694-0.888) in the External-1 and External-2, respectively. Our proposed ensemble model, integrating multiple base models and inputs from OCT analysis, demonstrates strong potential for leveraging OCT imaging in detecting both AD-dementia and early-stage AD, enabling opportunistic screening for AD during ophthalmic visits. Financial Disclosures: Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.
Key findings
- For detecting AD-dementia, the ensemble model achieved the area under the receiver operating characteristic curve (AUROC) of 0.943 (95% confidence interval, 0.906-0.980), 0.786 (95% confidence interval, 0.673-0.899), and 0.795 (95% confidence interval, 0.716-0.874) in the internal validation, External-1, and External-2, respectively.
- For detecting AD-MCI defined by PET biomarkers, the ensemble model achieved AUROCs of 0.787 (95% confidence interval, 0.643-0.931) and 0.791 (95% confidence interval, 0.694-0.888) in the External-1 and External-2, respectively.
- Our proposed ensemble model, integrating multiple base models and inputs from OCT analysis, demonstrates strong potential for leveraging OCT imaging in detecting both AD-dementia and early-stage AD, enabling opportunistic screening for AD during ophthalmic visits.
- Financial Disclosures: Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.
Why it matters
This study reports that an artificial intelligence model using eye scans could help detect Alzheimer's dementia and early-stage Alzheimer's, potentially during eye appointments. It is a diagnostic approach only and does not test any treatment, cure or prevention.
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Study details
- Study designcase-control study
- Participants190
- Evidence strengthModerate
How this study scored 54/100
Published in a peer-reviewed journal, and it is a case-control study. Scored zero for effect reported and randomised / blinded because the record does not state it.
| Component | Points | Why |
|---|---|---|
| Journal tier | 7 / 10 | Tier 3 — peer-reviewed journal (Ophthalmology Science) |
| Journal's citation record | 0 / 4 | Ophthalmology Science: journal h-index 39 (OpenAlex, 2026-10-29) |
| Study design | 6 / 12 | A case-control study |
| Strength of evidence | 3 / 5 | Rated “moderate” in our summary |
| Peer-review validation | 10 / 10 | Peer-reviewed. Published as an article in a named peer-reviewed journal. |
| How recent | 5 / 5 | 2026 — within 1 year(s) of the newest study here |
| Sample size | 2 / 4 | 190 participants |
| Effect reported | 0 / 3 | No effect size reported — scores zero (not stated in the record — scored 0) |
| Studied in people | 3 / 3 | Studied in people (participant count stated) |
| Randomised / blinded | 0 / 2 | No randomisation or blinding stated — scores zero (not stated in the record — scored 0) |
| Times cited | 1 / 7 | Cited 3 times (OpenAlex, 2026-10-10) |
| Citations per year | 1 / 5 | 1.5 citations a year over 2 year(s) since 2026 |
| Impact for its field and year | 4 / 6 | Cited 14.2× the average for papers of its field and year (OpenAlex FWCI) |
| Cited by studies here | 0 / 6 | No other study in this library cites it |
| Still being cited | 1 / 4 | Cited 3 times in 2024–2026 (2026 still in progress; OpenAlex) |
| Senior author's track record | 2 / 4 | Last-listed author Carol Yim-Lui Cheung: h-index 41 (OpenAlex, whole career) |
| Institution's track record | 2 / 3 | Johns Hopkins University: institution h-index 2,306 (OpenAlex) |
| Multi-centre collaboration | 3 / 3 | OpenAlex lists 12 institution(s) in 4 countries |
| Indexed in PubMed | 2 / 2 | Indexed in PubMed (PMID 41717239) |
| Free to read | 2 / 2 | Free to read |
| Total | 54 / 100 | — |
What each of these 20 components measures, and what this score is not →
Read the original
- DOI: 10.1016/j.xops.2026.101066
- PubMed: 41717239
- Original source →
- Free full text: Ophthalmology Science →
Full text: free to read — OpenAlex lists this copy as free to read: the link above (checked 6 Feb 1020).
Cite this study APA, Vancouver, BibTeX · download .bib or .ris
Built from the record alzhub holds for this paper, not looked up. Volume, issue and page numbers are not held in the record. The record's author list ends in “et al.”, so not every author is named. Check the citation against the original before you use it.
APA 7th
Ran, A. R., Hu, X., Hui, H. Y., Dai, J., Chan, V. T., Ho, K., et al. (2026). An Ensemble Learning Artificial Intelligence Model for Alzheimer's Disease Detection Using OCT. Ophthalmology Science. https://doi.org/10.1016/j.xops.2026.101066
Vancouver
Ran AR, Hu X, Hui HY, Dai J, Chan VT, Ho K, et al. An Ensemble Learning Artificial Intelligence Model for Alzheimer's Disease Detection Using OCT. Ophthalmology Science. 2026. doi:10.1016/j.xops.2026.101066. PMID: 41717239.
BibTeX
@article{ran2026-41717239,
author = {Ran, An Ran and Hu, Xiaoyan and Hui, Herbert Y.H. and Dai, Jiajia and Chan, Victor T.T. and Ho, Ko and Au, Lisa WC and Ng, Chak Fung and others},
title = {{An Ensemble Learning Artificial Intelligence Model for Alzheimer's Disease Detection Using OCT}},
journal = {Ophthalmology Science},
year = {2026},
doi = {10.1016/j.xops.2026.101066},
pmid = {41717239},
url = {https://doi.org/10.1016/j.xops.2026.101066}
}
Studies this one cites
Referenced by this study and also in the alzhub library, so you can read them here.