METHODS OF INFORMATION TECHNOLOGY IN THEPREVENTION OF COGNITIVE DYSFUNCTION IN PATIENTS WITH HYPERTENSION
Bibliographic record
Abstract
Objective: to analyze electroencephalographic parameters in patients with hypertension and cognitive complaints receiving standard antihypertensive therapy, without concomitant cardiovas-cular disease, for the purpose of early diagnosis of brain damage as the main target organ in hy-pertension. Materials and methods: 135 people were examined (95 people with arterial hyperten-sion and 43 potentially healthy). The average age of patients is 63±8.2 years. As a result of the diagnosis, patients were distributed as follows: no cognitive impairment-82 people (60.7 %), mild cognitive impairment – 32 people (23.7 %), moderate cognitive impairment – 21 people (15.6 %). The studies were carried out on the apparatus "Encephalan-EEGR-19/26". Results: after the treatment, the majority of patients had a reduction of pre-reported complaints, an increase on the "Montreal scale" from 1 to 2 points, a decrease in anxiety and depression on the "Hospital scale", an increase in indices on SF-36. According to EEG data, there was an increase in the frequency of the main alpha rhythm and the total bioelectric power of the rhythm, the appearance of a pro-nounced spectral peak in the alpha range, a decrease in the power of the slow-wave rhythm in the anterior parts, which also indicates a positive dynamics that correlates with clinical data and test data. Conclusions: the study established the diagnostic value of quantitative processing of elec-troencephalogram (the frequency of the main rhythm, the power of the theta and Delta rhythms in the anterior parts, the total power of the b. e. a.), which suggest the need for additional therapy to standard antihypertensive treatment.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".