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Discovering Dynamic Models from Clinical Data Using Neural-PK/PD

This talk demonstrates how the neural network functionalities of Wolfram Language have enabled development of a neural-PK/PD modeling framework that can now be more efficiently assembled from component layers into network submodules. This improves on other models' ability to predict patient response time within a course of treatment.

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