Description: DeepPumas is a powerful tool that bridges the gap between mechanistic, statistical, and machine-learning modeling. This hands-on workshop will introduce participants to the core concepts behind DeepPumas and its potential to transform decision-making in the healthcare space. By seamlessly embedding machine learning methodology into nonlinear mixed-effect models, DeepPumas enables the simultaneous utilization of domain-specific knowledge and available data for model identification. In this workshop, we will learn about NeuralODEs, universal differential equations, and scientific machine learning and how these can be leveraged to discover unknown dynamics driving disease progression and treatment response. We will then see how DeepNLME expands these concepts to include random effects which lets us discover individualizable models that can tell us something about not only the measurements in our data but about the patients whose outcomes we care about. Furthermore, we will learn how to leverage machine learning to identify prognostic factors from complex data. After gaining theoretical understanding and practical experience in using these new technologies, we will explore different use cases to understand how DeepPumas is poised to transform the role of data and modeling in healthcare.

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November 9-10, 2024

8 am - 5 pm

Presenters:

Niklas Korsbo, PhD

Mohamed Tarek, PhD

Vijay Ivaturi, PhD

Andreas Noack, PhD