Neuropsychological characteristics of individuals with mild cognitive impairment
Bibliographic record
Abstract
Introduction As the population ages, cognitive impairment is prevalent among older adults and this may cause a huge burden to society. In order to take precautions effectively, we need to understand the characteristics of cognitive function of older adults, especially the individuals with mild cognitive impairment (MCI). Objectives To explore the characteristics of cognitive function changes in individuals with mild cognitive impairment. Methods A total of 108 individuals with MCI as MCI group and 108 volunteers as control group were recruited in the study. The age, gender and years of schooling were matched between the two groups. The cognitive function was evaluated with the Montreal Cognitive Assessment (MoCA). Results Individuals of MCI group performed poorer than those of control group on executive function, attention, calculation, language and delayed memory. The difference between the two groups was statistically significant (P < 0.05). The cognitive impairment in participants with MCI were delayed memory (100%), language (75%), executive function (66.7%), attention (44%) and calculation (20.4%). Conclusions The impairment of memory, language and executive function is the primary characteristics in individuals with MCI. Individuals with MCI have similar characteristics with early stage Alzheimer's disease (AD). We should take preventive measures to improve or delay AD. Disclosure of interest The authors have not supplied their declaration of competing interest.
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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) | 0.002 | 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".