https://www.selleckchem.com/products/mi-503.html
Vagus nerve stimulation (VNS) is an emerging therapeutic strategy for pathological conditions in a variety of diseases; however, several challenges arise for applying this stimulation paradigm in automated closed-loop control. In this work, we propose a data driven approach for predicting the impact of VNS on physiological variables. We apply this approach on a synthetic dataset created with a physiological model of a rat heart. Through training several neural network models, we found that a long short term memory (LSTM) architecture gav
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