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Development and validation of a reinforcement learning algorithm to dynamically optimize mechanical ventilation in critical care
The aim of this work was to develop and evaluate the reinforcement learning algorithm VentAI, which is able to suggest a dynamically optimized mechanical ventilation regime for critically-ill patients. We built, validated and tested its performance on 11,943 events of volume-controlled mechanical ve...
| Autores principales: | , , , , , , , , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Nature Publishing Group UK
2021
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7895944/ https://www.ncbi.nlm.nih.gov/pubmed/33608661 http://dx.doi.org/10.1038/s41746-021-00388-6 |