FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W4296564712> ?p ?o ?g. }

• W4296564712 abstract "Abstract Purpose Serum lactate levels are considered a biomarker of tissue hypoxia. In sepsis or septic shock patients as suggested by The Surviving Sepsis Campaign serum lactate levels should be assessed and early lactate clearance-directed therapy is associated with decreased mortality. Monitoring a patient's vital parameters and repeatedly done blood analysis may have deleterious effects on the patient and brings an economical burden. Machine learning algorithms and trend analysis are gaining importance to overcome these unwanted facts. In this context, we aimed to investigate if an artificial intelligence approach can predict lactate trends from non-invasive clinical variables of patients with sepsis. Methods In this retrospective study, adult patients with sepsis from the MIMIC-IV dataset who had at least two serum lactate measurements recorded within the first 6 hours of sepsis diagnosis and who also has an ICU length of stay ≥ 24 hours are evaluated and ≥1mmol/l change is considered as a trend indicator. For prediction of lactate trend Naïve Bayes, J48 Decision Tree, Logistic Regression, Random Forest, and Logistic Model Tree (LMT) classifiers are evaluated. Results LMT algorithm outperformed other classifiers (AUC= 0.832). J48 decision tree performed worse when predicting constant lactate trend. LMT algorithm with 4 features (heart rate, oxygen saturation, lactate value before sepsis diagnosis, and time interval variables) achieved 0.821 in terms of AUC. Conclusion We can say that machine learning models that employ logistic regression architectures, i.e. LMT algorithm achieved good results in lactate trend prediction tasks can be effectively used to assess the state of the patient whether it is stable or improving." @default.
• W4296564712 created "2022-09-21" @default.
• W4296564712 creator A5029360653 @default.
• W4296564712 creator A5058021709 @default.
• W4296564712 creator A5061700604 @default.
• W4296564712 creator A5061999270 @default.
• W4296564712 creator A5063767889 @default.
• W4296564712 creator A5068447287 @default.
• W4296564712 creator A5073628091 @default.
• W4296564712 date "2022-09-21" @default.
• W4296564712 modified "2023-10-18" @default.
• W4296564712 title "Using machine learning methods to predict the lactate trend of sepsis patients in the ICU" @default.
• W4296564712 cites W2014802742 @default.
• W4296564712 cites W2033518318 @default.
• W4296564712 cites W2111026086 @default.
• W4296564712 cites W2152154097 @default.
• W4296564712 cites W2158623850 @default.
• W4296564712 cites W2164529528 @default.
• W4296564712 cites W2280404143 @default.
• W4296564712 cites W2421793612 @default.
• W4296564712 cites W2614741637 @default.
• W4296564712 cites W2735761750 @default.
• W4296564712 cites W2737554657 @default.
• W4296564712 cites W2772748224 @default.
• W4296564712 cites W2786635213 @default.
• W4296564712 cites W2799662739 @default.
• W4296564712 cites W2809789609 @default.
• W4296564712 cites W2895786840 @default.
• W4296564712 cites W2896938420 @default.
• W4296564712 cites W2902220494 @default.
• W4296564712 cites W2903091960 @default.
• W4296564712 cites W2909576544 @default.
• W4296564712 cites W2915869464 @default.
• W4296564712 cites W2939945347 @default.
• W4296564712 cites W2944396597 @default.
• W4296564712 cites W2965956687 @default.
• W4296564712 cites W2980978739 @default.
• W4296564712 cites W2981512873 @default.
• W4296564712 cites W3005700774 @default.
• W4296564712 cites W3081126190 @default.
• W4296564712 cites W3094171951 @default.
• W4296564712 cites W3097666541 @default.
• W4296564712 cites W3117160760 @default.
• W4296564712 cites W3156315234 @default.
• W4296564712 cites W3158391672 @default.
• W4296564712 cites W3163428870 @default.
• W4296564712 cites W3184364136 @default.
• W4296564712 cites W3194296141 @default.
• W4296564712 cites W3203103016 @default.
• W4296564712 cites W3213024030 @default.
• W4296564712 cites W4205790295 @default.
• W4296564712 cites W4292229870 @default.
• W4296564712 doi "https://doi.org/10.21203/rs.3.rs-1855422/v2" @default.
• W4296564712 hasPublicationYear "2022" @default.
• W4296564712 type Work @default.
• W4296564712 citedByCount "0" @default.
• W4296564712 crossrefType "posted-content" @default.
• W4296564712 hasAuthorship W4296564712A5029360653 @default.
• W4296564712 hasAuthorship W4296564712A5058021709 @default.
• W4296564712 hasAuthorship W4296564712A5061700604 @default.
• W4296564712 hasAuthorship W4296564712A5061999270 @default.
• W4296564712 hasAuthorship W4296564712A5063767889 @default.
• W4296564712 hasAuthorship W4296564712A5068447287 @default.
• W4296564712 hasAuthorship W4296564712A5073628091 @default.
• W4296564712 hasBestOaLocation W42965647121 @default.
• W4296564712 hasConcept C119857082 @default.
• W4296564712 hasConcept C12267149 @default.
• W4296564712 hasConcept C126322002 @default.
• W4296564712 hasConcept C151730666 @default.
• W4296564712 hasConcept C151956035 @default.
• W4296564712 hasConcept C154945302 @default.
• W4296564712 hasConcept C169258074 @default.
• W4296564712 hasConcept C177713679 @default.
• W4296564712 hasConcept C2778384902 @default.
• W4296564712 hasConcept C2779343474 @default.
• W4296564712 hasConcept C41008148 @default.
• W4296564712 hasConcept C52001869 @default.
• W4296564712 hasConcept C52003472 @default.
• W4296564712 hasConcept C71924100 @default.
• W4296564712 hasConcept C84525736 @default.
• W4296564712 hasConcept C86803240 @default.
• W4296564712 hasConceptScore W4296564712C119857082 @default.
• W4296564712 hasConceptScore W4296564712C12267149 @default.
• W4296564712 hasConceptScore W4296564712C126322002 @default.
• W4296564712 hasConceptScore W4296564712C151730666 @default.
• W4296564712 hasConceptScore W4296564712C151956035 @default.
• W4296564712 hasConceptScore W4296564712C154945302 @default.
• W4296564712 hasConceptScore W4296564712C169258074 @default.
• W4296564712 hasConceptScore W4296564712C177713679 @default.
• W4296564712 hasConceptScore W4296564712C2778384902 @default.
• W4296564712 hasConceptScore W4296564712C2779343474 @default.
• W4296564712 hasConceptScore W4296564712C41008148 @default.
• W4296564712 hasConceptScore W4296564712C52001869 @default.
• W4296564712 hasConceptScore W4296564712C52003472 @default.
• W4296564712 hasConceptScore W4296564712C71924100 @default.
• W4296564712 hasConceptScore W4296564712C84525736 @default.
• W4296564712 hasConceptScore W4296564712C86803240 @default.
• W4296564712 hasLocation W42965647121 @default.
• W4296564712 hasOpenAccess W4296564712 @default.
• W4296564712 hasPrimaryLocation W42965647121 @default.

• next