FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2079083604> ?p ?o ?g. }

• W2079083604 endingPage "1150" @default.
• W2079083604 startingPage "1146" @default.
• W2079083604 abstract "Decisions about which patients to admit to intensive care and how long to keep them there are difficult. A flexible computer-based mathematical model which is sensitive to the complexity of intensive care medicine, and which accurately models prognosis, seems highly desirable.We have created, optimised by genetic algorithms, trained, and evaluated the performance of an artificial neural network (ANN) in the clinical setting of systemic inflammatory response syndrome and haemodynamic shock. 258 patients were selected from an intensive care database of 4484 patients at a London teaching hospital and randomised to a network training set (168) and a test set (90). The outcome evaluated was death during that hospital admission and the performance of the neural net was compared (by receiver operating characteristic [ROC] curves and by Brier scores) with that of a logistic regression model.Artificial neural network performance increased with successive generations; the best-performing ANN was created after 7 generations and predicted outcome more accurately than the logistic regression model (ROC curve area 0.863 vs 0.753).In this study, ANNs have lent themselves particularly well to modelling a complex clinical situation; we suggest that this relates to their inherently flexible nature which accommodates interactions between the clinical input fields. In addition, we have demonstrated the value of a second computational technique (genetic algorithms) in tuning ANN performance. These techniques can potentially be implemented in individual intensive care units; the outcome models which they will generate will be sensitive to local practice. Analysis of such accurate clinical outcome models may empower clinicians with a hitherto unappreciated degree of insight into those elements of their clinical practice which are most relevant to their patients' outcome." @default.
• W2079083604 created "2016-06-24" @default.
• W2079083604 creator A5033883688 @default.
• W2079083604 creator A5051933686 @default.
• W2079083604 creator A5079578424 @default.
• W2079083604 creator A5081484617 @default.
• W2079083604 date "1996-04-01" @default.
• W2079083604 modified "2023-10-14" @default.
• W2079083604 title "Prediction of outcome in critically ill patients using artificial neural network synthesised by genetic algorithm" @default.
• W2079083604 cites W134710876 @default.
• W2079083604 cites W1968114652 @default.
• W2079083604 cites W1984420781 @default.
• W2079083604 cites W1996970972 @default.
• W2079083604 cites W2019734720 @default.
• W2079083604 cites W2023691053 @default.
• W2079083604 cites W2033339846 @default.
• W2079083604 cites W2033925475 @default.
• W2079083604 cites W2052661232 @default.
• W2079083604 cites W2062210734 @default.
• W2079083604 cites W2063655653 @default.
• W2079083604 cites W2065699321 @default.
• W2079083604 cites W2067747050 @default.
• W2079083604 cites W2082678622 @default.
• W2079083604 cites W2093846540 @default.
• W2079083604 cites W2100078522 @default.
• W2079083604 cites W2123715374 @default.
• W2079083604 cites W2131088864 @default.
• W2079083604 cites W2156133368 @default.
• W2079083604 cites W4247943214 @default.
• W2079083604 cites W4293242440 @default.
• W2079083604 cites W4361865037 @default.
• W2079083604 doi "https://doi.org/10.1016/s0140-6736(96)90609-1" @default.
• W2079083604 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/8609749" @default.
• W2079083604 hasPublicationYear "1996" @default.
• W2079083604 type Work @default.
• W2079083604 sameAs 2079083604 @default.
• W2079083604 citedByCount "224" @default.
• W2079083604 countsByYear W20790836042012 @default.
• W2079083604 countsByYear W20790836042013 @default.
• W2079083604 countsByYear W20790836042014 @default.
• W2079083604 countsByYear W20790836042015 @default.
• W2079083604 countsByYear W20790836042016 @default.
• W2079083604 countsByYear W20790836042017 @default.
• W2079083604 countsByYear W20790836042018 @default.
• W2079083604 countsByYear W20790836042019 @default.
• W2079083604 countsByYear W20790836042020 @default.
• W2079083604 countsByYear W20790836042021 @default.
• W2079083604 countsByYear W20790836042022 @default.
• W2079083604 countsByYear W20790836042023 @default.
• W2079083604 crossrefType "journal-article" @default.
• W2079083604 hasAuthorship W2079083604A5033883688 @default.
• W2079083604 hasAuthorship W2079083604A5051933686 @default.
• W2079083604 hasAuthorship W2079083604A5079578424 @default.
• W2079083604 hasAuthorship W2079083604A5081484617 @default.
• W2079083604 hasConcept C119857082 @default.
• W2079083604 hasConcept C144237770 @default.
• W2079083604 hasConcept C148220186 @default.
• W2079083604 hasConcept C151956035 @default.
• W2079083604 hasConcept C154945302 @default.
• W2079083604 hasConcept C177264268 @default.
• W2079083604 hasConcept C177713679 @default.
• W2079083604 hasConcept C199360897 @default.
• W2079083604 hasConcept C2987404301 @default.
• W2079083604 hasConcept C33923547 @default.
• W2079083604 hasConcept C35405484 @default.
• W2079083604 hasConcept C41008148 @default.
• W2079083604 hasConcept C50644808 @default.
• W2079083604 hasConcept C58471807 @default.
• W2079083604 hasConcept C71924100 @default.
• W2079083604 hasConcept C8880873 @default.
• W2079083604 hasConceptScore W2079083604C119857082 @default.
• W2079083604 hasConceptScore W2079083604C144237770 @default.
• W2079083604 hasConceptScore W2079083604C148220186 @default.
• W2079083604 hasConceptScore W2079083604C151956035 @default.
• W2079083604 hasConceptScore W2079083604C154945302 @default.
• W2079083604 hasConceptScore W2079083604C177264268 @default.
• W2079083604 hasConceptScore W2079083604C177713679 @default.
• W2079083604 hasConceptScore W2079083604C199360897 @default.
• W2079083604 hasConceptScore W2079083604C2987404301 @default.
• W2079083604 hasConceptScore W2079083604C33923547 @default.
• W2079083604 hasConceptScore W2079083604C35405484 @default.
• W2079083604 hasConceptScore W2079083604C41008148 @default.
• W2079083604 hasConceptScore W2079083604C50644808 @default.
• W2079083604 hasConceptScore W2079083604C58471807 @default.
• W2079083604 hasConceptScore W2079083604C71924100 @default.
• W2079083604 hasConceptScore W2079083604C8880873 @default.
• W2079083604 hasIssue "9009" @default.
• W2079083604 hasLocation W20790836041 @default.
• W2079083604 hasLocation W20790836042 @default.
• W2079083604 hasOpenAccess W2079083604 @default.
• W2079083604 hasPrimaryLocation W20790836041 @default.
• W2079083604 hasRelatedWork W1774890144 @default.
• W2079083604 hasRelatedWork W1875926297 @default.
• W2079083604 hasRelatedWork W2043644439 @default.
• W2079083604 hasRelatedWork W2051201630 @default.
• W2079083604 hasRelatedWork W2082471284 @default.
• W2079083604 hasRelatedWork W2320542465 @default.
• W2079083604 hasRelatedWork W2728311169 @default.

• next