[P1–451]: MEASURING SYNTHETIC AGE VIA MORPHOMETRY AS A PROXY OF BRAIN HEALTH IN INDIVIDUALS WITH CLINICAL ALZHEIMER'S DISEASE
Bibliographic record
Abstract
We developed a technique to determine the synthetic age (as opposed to chronological age) of an individual, based on brain morphometry. We tested this paradigm on individuals with clinical Alzheimer's disease (AD). We predicted age using a model built from T1-weighted MRIs of 2,718 healthy individuals aged 18 to 94 years processed with FreeSurfer version 5.3. We built a ridge regression model using data from the output statistics (aseg, aparc. DKTatlas40, entorhinal_exvivo, and wmparc) and 10-fold cross-validation. The predicted synthetic brain age model was then applied to two independent test samples: 50 cognitively healthy controls and 50 individuals with mild AD from the ADNI-2 dataset. In healthy controls, the correlation between chronological and synthetic age was 0.93 (p < .00001; Figure 1) in the cross-validation model and 0.92 (p < .00001; Figure 2) in the independent test sample; whereas in individuals with AD the correlation was 0.28 (p = .049; Figure 3). The mean difference between chronological and predicted age was -0.3 years (SD: 8.4) in healthy controls and 1.6 years (SD: 10.3) in AD.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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 teacher head, 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".