Correlation between PET-derived cerebral amyloid status and retinal image features using a hyperspectral fundus camera
Bibliographic record
Abstract
This study, investigates the relationship between retinal image features and β-amyloid (Aβ) burden in the brain with the aim of developing a non-invasive early detection method for Alzheimer’s disease (AD). 172 retinal images from 20 clinically probable AD and 45 age-matched control cases were acquired using a hyper spectral imaging system. Brain Aβ accumulation was estimated from amyloid PET imaging. Spatial and spectral features from the hyperspectral retinal images were calculated including vessels tortuosity and image textures at different anatomical regions. Retinal veins of amyloid positive subjects (Aβ+) showed a higher mean tortuosity compared to the amyloid negative subjects (p<2.4e-7). Furthermore, a significant difference between texture measures of retinal arteries and their adjacent regions were observed in Aβ+ subjects when compared to the Aβ- (p<1.3e-5).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".