FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W4282833873> ?p ?o ?g. }

• W4282833873 endingPage "210" @default.
• W4282833873 startingPage "201" @default.
• W4282833873 abstract "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, VO 2 and VCO 2 plus three model-defining parameters: shunt, log SD and mean V/Q. From these inputs the model produced paired arterial blood gases, first with the inspired O 2 fraction (FiO 2 ) adjusted to arterial saturation (SaO 2 ) = 0.90, and second with FiO 2 increased by 0.1. ‘Stacked regressor’ ML ensembles were trained/validated on 90% of this dataset. The remainder with shunt, log SD, and mean ‘held back’ formed the test-set. ‘Two-Point’ ML estimates of shunt, log SD and mean utilized data from both FiO 2 settings. ‘Single-Point’ estimates used only data from SaO 2 = 0.90. From 3454 test gas exchange scenarios, two-point shunt, log SD and mean estimates produced linear regression models versus true values with slopes ~ 1.00, intercepts ~ 0.00 and R 2 ~ 1.00. Kernel density and Bland–Altman plots confirmed close agreement. Single-point estimates were less accurate: R 2 = 0.77–0.89, slope = 0.991–0.993, intercept = 0.009–0.334. ML applications using blood gas, indirect calorimetry, and cardiac output data can quantify pulmonary gas exchange in terms describing a 20 compartment V/Q model of pulmonary blood flow. High fidelity reports require data from two FiO 2 settings." @default.
• W4282833873 created "2022-06-15" @default.
• W4282833873 creator A5005827520 @default.
• W4282833873 creator A5035300677 @default.
• W4282833873 creator A5067400459 @default.
• W4282833873 creator A5091816701 @default.
• W4282833873 date "2022-06-13" @default.
• W4282833873 modified "2023-09-28" @default.
• W4282833873 title "Pulmonary gas exchange evaluated by machine learning: a computer simulation" @default.
• W4282833873 cites W1503048361 @default.
• W4282833873 cites W1579711531 @default.
• W4282833873 cites W1973392033 @default.
• W4282833873 cites W1998293264 @default.
• W4282833873 cites W1998442387 @default.
• W4282833873 cites W1999760244 @default.
• W4282833873 cites W2000566182 @default.
• W4282833873 cites W2015795623 @default.
• W4282833873 cites W2041400770 @default.
• W4282833873 cites W2043355214 @default.
• W4282833873 cites W2066585090 @default.
• W4282833873 cites W2068043518 @default.
• W4282833873 cites W2075584215 @default.
• W4282833873 cites W2089201245 @default.
• W4282833873 cites W2095973298 @default.
• W4282833873 cites W2098745598 @default.
• W4282833873 cites W2106538411 @default.
• W4282833873 cites W2130251024 @default.
• W4282833873 cites W2149451908 @default.
• W4282833873 cites W2155332412 @default.
• W4282833873 cites W2171446894 @default.
• W4282833873 cites W2179754435 @default.
• W4282833873 cites W2180221472 @default.
• W4282833873 cites W2218766103 @default.
• W4282833873 cites W2346391051 @default.
• W4282833873 cites W2793095228 @default.
• W4282833873 cites W2893877102 @default.
• W4282833873 cites W2936573766 @default.
• W4282833873 cites W2953592273 @default.
• W4282833873 cites W3004650430 @default.
• W4282833873 cites W3014250429 @default.
• W4282833873 cites W3119298422 @default.
• W4282833873 cites W3177063793 @default.
• W4282833873 cites W3207706392 @default.
• W4282833873 cites W4229804136 @default.
• W4282833873 cites W4249081408 @default.
• W4282833873 cites W57514826 @default.
• W4282833873 doi "https://doi.org/10.1007/s10877-022-00879-1" @default.
• W4282833873 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/35691965" @default.
• W4282833873 hasPublicationYear "2022" @default.
• W4282833873 type Work @default.
• W4282833873 citedByCount "1" @default.
• W4282833873 countsByYear W42828338732023 @default.
• W4282833873 crossrefType "journal-article" @default.
• W4282833873 hasAuthorship W4282833873A5005827520 @default.
• W4282833873 hasAuthorship W4282833873A5035300677 @default.
• W4282833873 hasAuthorship W4282833873A5067400459 @default.
• W4282833873 hasAuthorship W4282833873A5091816701 @default.
• W4282833873 hasBestOaLocation W42828338731 @default.
• W4282833873 hasConcept C105795698 @default.
• W4282833873 hasConcept C136229726 @default.
• W4282833873 hasConcept C164705383 @default.
• W4282833873 hasConcept C178853913 @default.
• W4282833873 hasConcept C2779537118 @default.
• W4282833873 hasConcept C2779589923 @default.
• W4282833873 hasConcept C2780968331 @default.
• W4282833873 hasConcept C2989005 @default.
• W4282833873 hasConcept C33923547 @default.
• W4282833873 hasConcept C42219234 @default.
• W4282833873 hasConcept C71924100 @default.
• W4282833873 hasConceptScore W4282833873C105795698 @default.
• W4282833873 hasConceptScore W4282833873C136229726 @default.
• W4282833873 hasConceptScore W4282833873C164705383 @default.
• W4282833873 hasConceptScore W4282833873C178853913 @default.
• W4282833873 hasConceptScore W4282833873C2779537118 @default.
• W4282833873 hasConceptScore W4282833873C2779589923 @default.
• W4282833873 hasConceptScore W4282833873C2780968331 @default.
• W4282833873 hasConceptScore W4282833873C2989005 @default.
• W4282833873 hasConceptScore W4282833873C33923547 @default.
• W4282833873 hasConceptScore W4282833873C42219234 @default.
• W4282833873 hasConceptScore W4282833873C71924100 @default.
• W4282833873 hasFunder F4320320984 @default.
• W4282833873 hasIssue "1" @default.
• W4282833873 hasLocation W42828338731 @default.
• W4282833873 hasLocation W42828338732 @default.
• W4282833873 hasLocation W42828338733 @default.
• W4282833873 hasLocation W42828338734 @default.
• W4282833873 hasOpenAccess W4282833873 @default.
• W4282833873 hasPrimaryLocation W42828338731 @default.
• W4282833873 hasRelatedWork W196465352 @default.
• W4282833873 hasRelatedWork W2184614556 @default.
• W4282833873 hasRelatedWork W2350092990 @default.
• W4282833873 hasRelatedWork W2365698109 @default.
• W4282833873 hasRelatedWork W2377116287 @default.
• W4282833873 hasRelatedWork W2389543151 @default.
• W4282833873 hasRelatedWork W2411600967 @default.
• W4282833873 hasRelatedWork W2412821278 @default.
• W4282833873 hasRelatedWork W2490860824 @default.
• W4282833873 hasRelatedWork W2883249017 @default.

• next