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| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Thomas J., Morgan | - |
| dc.contributor.author | Adrian N., Langley | - |
| dc.contributor.author | Robin D. C., Barrett | - |
| dc.date.accessioned | 2023-03-24T07:20:02Z | - |
| dc.date.available | 2023-03-24T07:20:02Z | - |
| dc.date.issued | 2023 | - |
| dc.identifier.uri | https://link.springer.com/article/10.1007/s10877-022-00879-1 | - |
| dc.identifier.uri | https://dlib.phenikaa-uni.edu.vn/handle/PNK/7145 | - |
| dc.description | CC BY | vi |
| dc.description.abstract | 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. | vi |
| dc.language.iso | vi | vi |
| dc.publisher | Springer | vi |
| dc.subject | machine learning | vi |
| dc.subject | ICU | vi |
| dc.title | Pulmonary gas exchange evaluated by machine learning a computer simulation | vi |
| dc.type | Book | vi |
| Appears in Collections | ||
| OER- Y học- Điều dưỡng | ||
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