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About Combining Machine Learning and Agent-Based Modeling To Study Biomedical Systems
This document discusses combining machine learning and agent-based modeling to study biomedical systems. It begins with an overview of agent-based modeling, noting it takes a bottom-up approach by defining rules for individual agents that can then be used to simulate complex systems. It then introduces machine learning and how it can help infer optimal rules for agent-based models from data in a synergistic way. The document provides examples of how machine learning can be applied to derive agent rules, calibrate models, explore parameter spaces, and generate training data, highlighting the potential for iterative integration of the two approaches across spatial scales from cellular to population levels.
Detailed Information
| Author: | ['Marcelo Marcy Majstruk Cimillo'] |
|---|---|
| Publication Year: | 2022 |
| Pages: | 33 |
| Language: | English |
| Format: | |
| Price: | FREE |
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