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Record W2774992753 · doi:10.3791/56365

MRI-guided Focused Ultrasound Thalamotomy for Patients with Medically-refractory Essential Tremor

2017· article· en· W2774992753 on OpenAlexaff
Ying Meng, Yuexi Huang, Benjamin Solomon, Kullervo Hynynen, Nadia Scantlebury, Michael L. Schwartz, Nir Lipsman

Bibliographic record

VenueJournal of Visualized Experiments · 2017
Typearticle
Languageen
FieldMedicine
TopicNeurological disorders and treatments
Canadian institutionsHealth Sciences CentreSunnybrook Health Science Centre
Fundersnot available
KeywordsEssential tremorMedicineThalamotomyDeep brain stimulationQuality of life (healthcare)PallidotomyFocused ultrasoundMovement disordersPhysical medicine and rehabilitationRadiologyUltrasoundPathologyParkinson's disease

Abstract

fetched live from OpenAlex

Essential tremor (ET) is the most common type of tremor in adults. While ET does not result in decreased life expectancy, the disabilities associated with ET can have a significant impact on quality of life, mood, functional activities, and socialization. Patients suffering from ET not sufficiently treated with first line medications may be eligible for alternative strategies such as deep brain stimulation, radiofrequency ablation, and MRI guided focused ultrasound (MRgFUS). High-intensity MRgFUS is an emerging modality to treat ET, its attraction for patients being that it is noninvasive and associated with short recovery time, as patients are home the day after treatment. While MRgFUS centers are still limited, it will become important for clinicians to consider MRgFUS as a treatment alternative, particularly in the case of a patient for whom open surgery is contraindicated. This article outlines the steps of patient selection, equipment setup, sonication, and post-treatment follow-up, as well as critical steps to be aware of when performing a MRgFUS procedure.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.181
Threshold uncertainty score0.678

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.032
GPT teacher head0.410
Teacher spread0.379 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations15
Published2017
Admission routes1
Has abstractyes

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