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Deep Brain Stimulation as a Treatment for Refractory Epilepsy: Review of the Current State-of-the-Art

2017· review· en· W2761499239 on OpenAlexaff
Malika P. Ganguli, A.R.M. Upton, Markad V. Kamath

Bibliographic record

VenueJournal of Long-Term Effects of Medical Implants · 2017
Typereview
Languageen
FieldMedicine
TopicNeurological disorders and treatments
Canadian institutionsMcMaster University
Fundersnot available
KeywordsDeep brain stimulationNeurostimulationEpilepsyMedicineRefractory (planetary science)DystoniaEpilepsy surgeryPopulationStimulationNeuromodulationParkinson's diseaseNeuroscienceIntensive care medicinePhysical medicine and rehabilitationAnesthesiaDiseasePsychologyPsychiatryInternal medicine

Abstract

fetched live from OpenAlex

Epilepsy affects ∼ 1% of the global population, and 33% of patients are nonresponsive to medication and must seek alternative treatment options. Alternative options such as surgery and ablation exist but are not appropriate treatment plans for some patients. Neurostimulation methods such as vagal nerve stimulation, responsive neural stimulation, and deep brain stimulation (DBS) are viable alternatives for medically refractory patients. DBS stimulation has been used in the treatment of Parkinson's disease, dystonia, and pain management. For the treatment of epilepsy, DBS has been found to be an effective treatment plan, with promising results of reduced seizure frequency and intensity. In this review, we discuss DBS surgery and equipment, mechanisms of DBS for epilepsy, and efficacy, technological specifications, and suggestions for future research. We also review a historical summary of experiments involving DBS for epilepsy. Our literature review suggests that further studies are warranted for medically refractory epilepsy using DBS.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.877
Threshold uncertainty score0.743

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.074
GPT teacher head0.439
Teacher spread0.364 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
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

Citations3
Published2017
Admission routes1
Has abstractyes

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