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Comparison of Machine Learning Surrogate Models for Prediction of Single-Fiber Activation in Deep Brain Stimulation

2026-05-15

Abstract excerpt

Machine-learning surrogate models are positioned to help optimize deep brain stimulation (DBS) usage by predicting neural activation in response to electrical stimulation, while minimizing tradeoffs between computational expense and accuracy. Previous work has developed high accuracy artificial neural network (ANN) and convolutional neural network (CNN) surrogate models that predict activation of individual, myeli...

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Literature Corpus work
e1f34429-3a23-5f40-b894-1e4dae528a69
DOI
10.64898/2026.05.12.724686
Open publication

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Comparison of Machine Learning Surrogate Models for Prediction of Single-Fiber Activation in Deep Brain StimulationDOI 10.64898/2026.05.12.724686
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