ArticleBioengineering & translational medicine2025
Transport physics-informed reinforcement learning agents deployed in standalone infusion pumps for managing multidrug delivery in critical care.
Article in Bioengineering & translational medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Transport physics-informed reinforcement learning agents deployed in standalone infusion pumps for managing multidrug delivery in critical care.Bioengineering & translational medicine · 2025Article
- A Method for Temporally Resolved Continuous Inline Measurement of Multiple Solute Concentrations With Microfluidic Spectroscopy.IEEE open journal of engineering in medicine and biology · 2025Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Managing delivery of complex multidrug infusions in anesthesia and critical care presents a significant clinical challenge. Current practices relying on manual control of infusion pumps often result in unpredictable drug delivery profiles and dosing errors-key issues highlighted by the United States Food and Drug Administration (FDA). To address these issues, we introduce the SMART (synchronized-pump management algorithms for reliable therapies) framework, a novel approach that leverages low Reynolds number drug transport physics and machine learning to accurately manage multidrug infusions in real-time. SMART is activated based on the Shafer number (
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Registered trials
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