Trustworthy AI-Driven Hospital Digital Twin Framework for Resource Allocation and Patient Flow Optimization

Hospitals worldwide face increasing operational complexity due to emergency department congestion, fluctuating patient demand, limited resources, and the need for real-time decision support. This paper proposes a Trustworthy AI-Driven Hospital Digital Twin Framework for intelligent resource allocation and patient flow optimization, integrating artificial intelligence forecasting, optimization algorithms, reinforcement learning, digital twin simulation, and AI assurance mechanisms into a unified operational intelligence architecture. The framework consists of five major layers: Hospital Data Integration, AI Prediction, Hospital Digital Twin, Decision Intelligence, and AI Assurance, establishing a research framework for trustworthy AI-enabled hospital operations.

• Rakesh Kumar Agrawal

Zenodo

Preprint

Agrawal, R. K. (2025). Trustworthy AI-Driven Hospital Digital Twin Framework for Resource Allocation and Patient Flow Optimization. Zenodo. https://doi.org/10.5281/zenodo.21943591

@article{agrawal2025hospitaldigitaltwin, title={Trustworthy AI-Driven Hospital Digital Twin Framework for Resource Allocation and Patient Flow Optimization}, author={Agrawal, Rakesh Kumar}, year={2025}, howpublished={Zenodo}, doi={10.5281/zenodo.21943591}}