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Validation of a Hospital Digital Twin with Machine Learning

arXiv 2303.04117 ↗First posted 7 Mar 2023cs.AI cs.LGcited by 0

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Abstract (arXiv)

Recently there has been a surge of interest in developing Digital Twins of process flows in healthcare to better understand bottlenecks and areas of improvement. A key challenge is in the validation process. We describe a work in progress for a digital twin using an agent based simulation model for determining bed turnaround time for patients in hospitals. We employ a strategy using machine learning for validating the model and implementing sensitivity analysis.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 2 of its 31 references that are in the map. First posted on arXiv 7 Mar 2023.

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References · 2

  1. 2017Consistent feature attribution for tree ensemblescited by 18
  2. 2020Quantifying Explainability of Saliency Methods in Deep Neural Networks with a Synthetic Datasetcited by 14

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