aceModerate evidence
Published recordHealthGood Space (a documented gain)
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Gamma knife thalamotomy for essential tremor: can machine learning predict tremor improvement on the day of treatment?
- Truvace record
- TRV-2026-2474raw data (JSON)
- Version
- v1Published
- First published
- Evidence type
- Observational study
- Sources
- 1 sourcePeer-reviewed
- sha256
- 068366ab8110…check it
Background Gamma Knife (GK) thalamotomy is a minimally invasive treatment option for medically refractory essential tremor (ET), but clinical improvement is typically delayed for several months. Machine learning may enable individualized prediction of treatment response using routinely available data at the time of treatment.Structured abstract. Methods We retrospectively analyzed 163 GK thalamotomy procedures performed in 139 patients with ET. A random forest model was developed using demographic, clinical, bas…
The gain
In a retrospective study of 139 essential tremor patients, a machine learning model using day-of-treatment data predicted tremor improvement after Gamma Knife thalamotomy with an R² of 0.79 and an average error of 16 percentage points.
What this doesn’t fix
The model was developed retrospectively and validated only by hold-out and cross-validation, and the exploratory prediction of time to benefit was weak, with an R² of 0.31.
Sources
1 on file- Acta Neurologica Belgicadoi:10.1007/s13760-026-03231-5
Cite this record
v1Truvace Impact Record TRV-2026-2474, v1: “Gamma knife thalamotomy for essential tremor: can machine learning predict tremor improvement on the day of treatment?.” Truvace, 2026-11-11. /record/TRV-2026-2474 (accessed on the day you copy it). sha256 068366ab81105b27…
Change history
1 versionEvery change made to this record since it was first published, and why. Nothing has changed since it went up.
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