A systematic review and meta-analysis of the preclinical and clinical results of low-field magnetic stimulation in cognitive disorders
Bibliographic record
Abstract
Cognitive disorders such as major depressive disorder and bipolar disorder severely compromise brain function and neuronal activity. Treatments to restore cognitive abilities can have severe side effects due to their intense and excitatory nature, in addition to the fact that they are expensive and invasive. Low-field magnetic stimulation (LFMS) is a novel non-invasive proposed treatment for cognitive disorders. It repairs issues in the brain by altering deep cortical areas with treatments of low-intensity magnetic stimulation. This paper aims to summarize the current literature on the effects and results of LFMS in cognitive disorders. We developed a search strategy to identify relevant studies utilizing LFMS and systematically searched eight scientific databases. Our review suggests that LFMS could be a viable and effective treatment for multiple cognitive disorders, especially major depressive disorder. Additionally, longer, more frequent, and more personalized LFMS treatments tend to be more efficacious.
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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 | 0.007 | 0.021 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.014 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".