Pulmonary gas exchange evaluated by machine learning a computer simulation
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Springer
2023
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Online Access: | https://link.springer.com/article/10.1007/s10877-022-00879-1 https://dlib.phenikaa-uni.edu.vn/handle/PNK/7145 |
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oai:localhost:PNK-71452023-03-24T07:20:03Z Pulmonary gas exchange evaluated by machine learning a computer simulation Thomas J., Morgan Adrian N., Langley Robin D. C., Barrett machine learning ICU CC BY Using computer simulation we investigated whether machine learning (ML) analysis of selected ICU monitoring data can quantify pulmonary gas exchange in multi-compartment format. A 21 compartment ventilation/perfusion (V/Q) model of pulmonary blood flow processed 34,551 combinations of cardiac output, hemoglobin concentration, standard P50, base excess, VO2 and VCO2 plus three model-defining parameters: shunt, log SD and mean V/Q. 2023-03-24T07:20:02Z 2023-03-24T07:20:02Z 2023 Book https://link.springer.com/article/10.1007/s10877-022-00879-1 https://dlib.phenikaa-uni.edu.vn/handle/PNK/7145 vi application/pdf Springer |
institution |
Digital Phenikaa |
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Digital Phenikaa |
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Vietnamese |
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machine learning ICU |
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machine learning ICU Thomas J., Morgan Adrian N., Langley Robin D. C., Barrett Pulmonary gas exchange evaluated by machine learning a computer simulation |
description |
CC BY |
format |
Book |
author |
Thomas J., Morgan Adrian N., Langley Robin D. C., Barrett |
author_facet |
Thomas J., Morgan Adrian N., Langley Robin D. C., Barrett |
author_sort |
Thomas J., Morgan |
title |
Pulmonary gas exchange evaluated by machine learning a computer simulation |
title_short |
Pulmonary gas exchange evaluated by machine learning a computer simulation |
title_full |
Pulmonary gas exchange evaluated by machine learning a computer simulation |
title_fullStr |
Pulmonary gas exchange evaluated by machine learning a computer simulation |
title_full_unstemmed |
Pulmonary gas exchange evaluated by machine learning a computer simulation |
title_sort |
pulmonary gas exchange evaluated by machine learning a computer simulation |
publisher |
Springer |
publishDate |
2023 |
url |
https://link.springer.com/article/10.1007/s10877-022-00879-1 https://dlib.phenikaa-uni.edu.vn/handle/PNK/7145 |
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1761278341590024192 |
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8.891145 |