Clinical relevance of the brain morphometric indicators for the Alzheimer’s disease diagnosis
Bibliographic record
Abstract
The purpose — to study the morphometric data of the brain in patients with Alzheimer’s disease (AD) as a possible additional instrumental paraclinical neuroimaging marker to verify the accuracy of the diagnosis. Material and methods. We examined 27 patients with Alzheimer’s disease: 14 (51,9%) men and 13 (45,1%) women, average age 74,5 ± 8,7 years with a probable diagnosis of Alzheimer’s disease, anamnestic type. All patients received standard combination therapy with anti-dementia drugs. The patients underwent magnetic resonance imaging of the brain, followed by automated image segmentation and neuropsychological examination using the Montreal scale for assessing cognitive functions. Results. In our study, no statistically significant correlations were found between the data of neuropsychological testing, educational level, age, gender, and volumes of gray and white matter of the brain. Conclusion. According to the study, indicators of the volume of gray and white matter of the brain are not recommended as an additional neuroimaging marker of AD.
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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 | 0.001 | 0.004 |
| 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) | 0.002 | 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".