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Predicting the location where a lost person could be found is crucial for
search and rescue operations with limited resources.
To improve the
precision and efficiency of these predictions,
simulated agents can be
created to emulate the behavior of the lost person.
Within this study,
we introduce an innovative agent-based model designed
to replicate diverse psychological profiles of lost persons,
allowing these agents to navigate real-world landscapes while making
decisions autonomously
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PopMedNet™ is an open-source application used to facilitate multi-site health data networks. It uses a distributed network design that enables data holders to retain full control of their data. Investigators send questions to data holders for review and response. PopMedNet eliminates the need for assembling patient records in a centralized repository, thus preserving patient privacy and confidentiality.
This Dataset contains sample data using the PCORnet Common Data Model for running the regression tests supplied with PopMedNet™.
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