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Record W2095533517 · doi:10.1155/2013/679389

rTMS as a Treatment of Alzheimer’s Disease with and without Comorbidity of Depression: A Review

2013· review· en· W2095533517 on OpenAlexafffund
Grant Rutherford, Rebecca Gole, Zahra Moussavi

Bibliographic record

VenueNeuroscience Journal · 2013
Typereview
Languageen
FieldNeuroscience
TopicTranscranial Magnetic Stimulation Studies
Canadian institutionsRiverview HospitalUniversity of Manitoba
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsComorbidityDepression (economics)DiseasePsychiatryMedicinePsychologyInternal medicineKeynesian economics

Abstract

fetched live from OpenAlex

With an ever-increasing population of Alzheimer's disease (AD) patients worldwide, a noninvasive treatment for AD is needed. In this paper, the application of repetitive transcranial magnetic stimulus (rTMS) as a treatment for patients with probable AD is compared to the application of rTMS as a treatment for depression. Comorbidity of depression and dementia is discussed, as well as possible links between the two diseases. The possible confounding antidepressant effects of rTMS on cognitive improvements in AD patients are discussed.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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.

Opus teacher head0.211
GPT teacher head0.411
Teacher spread0.199 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations23
Published2013
Admission routes2
Has abstractyes

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