ReviewEpilepsy currents
Machine Learning for Precision Epilepsy Surgery.
Review in Epilepsy currents. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
10 citing papers in PubMed.
- Clinical application of artificial intelligence technology in epilepsy.Acta epileptologica · 2026Review
- Fully automated three-dimensional deep learning-based magnetic resonance imaging segmentation of brain cavities in epilepsy surgery.Epilepsia · 2026Article
- Super-resolution for localizing electrode grids as small, deformable objects during epilepsy surgery using augmented reality headsets.International journal of computer assisted radiology and surgery · 2025Article
- Electroencephalography-driven brain-network models for personalized interpretation and prediction of neural oscillations.Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology · 2025Article
- Leveraging interictal multimodal features and graph neural networks for automated planning of epilepsy surgery.Brain communications · 2025Article
- Transforming neurosurgical approaches to Aicardi syndrome through Artificial Intelligence.Neurosurgical review · 2024Article
- The value of linear and non-linear quantitative EEG analysis in paediatric epilepsy surgery: a machine learning approach.Scientific reports · 2024Article
- Memristive Neural Networks for Predicting Seizure Activity.Sovremennye tekhnologii v meditsine · 2023Article
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Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Brain surgery offers the best chance of seizure-freedom for patients with focal drug-resistant epilepsy, but only 50% achieve sustained seizure-freedom. With the explosion of data collected during routine presurgical evaluations and recent advances in computational science, we now have a tremendous potential to achieve precision epilepsy surgery: a data-driven tailoring of surgical planning. This review highlights the clinical need, the relevant computational science focusing on machine learning, and discusses some specific applications in epilepsy surgery.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.