The impact of aerobic exercise combined and computer cognitive training on cognitive function in patients with mild cognitive impairment
Bibliographic record
Abstract
Objective To investigate the changes of cognitive function in patients with mild cognitive impairment after aerobic exercise combined and computer cognitive training. Methods Four hundred and twenty patients were divided into two groups by random digits table method. The control group(200 cases) received general health education and rehabilitation training. The intervention group(220 cases) received aerobic exercise combined and computer cognitive training. The patients were assessed with Montreal Cognitive Assessment (MoCA) to evaluate their cognition before training, as well as after training. Results After intervention, the scores of the MoCA total score, naming, attention, language, memory, and orientation in the intervention group were 24.12 ± 2.18, 2.77 ± 0.42, 5.05 ± 0.88, 2.75 ± 0.56, 3.18 ± 0.91, 4.68 ± 0.87, the control group were 21.13 ± 2.13, 2.45 ± 0.56, 4.71 ± 1.10, 2.35 ± 0.69, 2.43 ± 0.81, 4.48 ± 0.96. There were statistically significant differences between the two groups (t=-11.278~-0.543, P 0.05). Conclusions The application of aerobic exercise combined and computer cognitive training could improve the cognitive function. Key words: Mild cognitive impairment; Aerobic exercise; Cognitive function; Computerized cognitive training
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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 | 0.000 | 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".