arXiv: cs.AI preprintsInternational6 November 2026
Learning a patient world model for health system simulation in intensive care
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arXiv:2611.08392v1 Announce Type: new Abstract: Designing healthcare strategies requires anticipating their clinical and operational consequences before implementation, a task that often relies on health system simulation. Such a simulation necessitates modeling how patient states evolve and generate care demands. However, conventional approaches typically tailor compact state transitions to a single policy question and omit history-dependent dynamics, thus requiring the redefinition of states and transitions when there is a new question that entails different clinical information. We propose
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