贝叶斯优化
迷走神经电刺激
计算机科学
波形
神经调节
刺激
人工智能
医学
迷走神经
电信
内科学
雷达
作者
Lorenz Wernisch,Tristan Edwards,Antonin Berthon,Olivier Tessier-Lariviere,Elvijs Sarkans,Myrta Stoukidi,Pascal Fortier-Poisson,Max Pinkney,Michael Thornton,Catherine Hanley,Susannah Lee,Joel Jennings,Ben Appleton,Phillip Garsed,Bret Patterson,W. Buttinger,Samuel Gonshaw,M. Jakopec,Sudhakaran Shunmugam,Jorin Mamen
标识
DOI:10.1088/1741-2552/ad33ae
摘要
In bioelectronic medicine, neuromodulation therapies induce neural signals to the brain or organs, modifying their function. Stimulation devices capable of triggering exogenous neural signals using electrical waveforms require a complex and multi-dimensional parameter space to control such waveforms. Determining the best combination of parameters (waveform optimization or dosing) for treating a particular patient's illness is therefore challenging. Comprehensive parameter searching for an optimal stimulation effect is often infeasible in a clinical setting due to the size of the parameter space. Restricting this space, however, may lead to suboptimal therapeutic results, reduced responder rates, and adverse effects.
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