Determining the Amount of Anesthetic Medicine to Be Applied by Using Elman’s Recurrent Neural Networks via Resilient Back Propagation

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doi:10.1007/s10916-009-9262-0

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Determining the Amount of Anesthetic Medicine to Be Applied by Using Elman’s Recurrent Neural Networks via Resilient Back Propagation

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Year: 2009 Journal: Journal of Medical Systems Vol: 34 (4)Pages: 493-497 Publisher: Springer Science+Business Media

DOI: 10.1007/s10916-009-9262-0

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Keywords:

Sigmoid function Artificial neural network Backpropagation Computer science Layer (electronics) Nonlinear system Artificial intelligence Moment (physics) Power (physics) Function (biology) Anesthesia Medicine Materials science

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Determining the Amount of Anesthetic Medicine to Be Applied by Using Elman’s Recurrent Neural Networks via Resilient Back Propagation

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