FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2966790404> ?p ?o ?g. }

• W2966790404 abstract "Abstract The ability to accurately predict in-hospital mortality for patients at the time of admission could improve clinical and operational decision-making and outcomes. Few machine learning models have been developed to predict in-hospital death that are both broadly applicable to all adult patients across a health system and readily implementable, and, to the best of our knowledge, none have been implemented, evaluated prospectively, or externally validated. The primary objective of this study was to prospectively and externally validate a machine learning model that predicts in-hospital mortality for all adult patients at the time of hospital admission. Model performance was quantified using the area under the receiver operating characteristic curve (AUROC) and area under the precision recall curve (AUPRC). Secondary objectives were to design the model using commonly available EHR data and accessible computational methods. A total of 75,247 hospital admissions (median [IQR] age 59.5 [29.0] years; male [45.9%]) were included in the study. The in-hospital mortality rates for the training validation, retrospective validations at Hospitals A, B, and C, and prospective validation cohorts, respectively, were 3.0%, 2.7%, 1.8%, 2.1%, and 1.6%. The area under the receiver operating characteristic curves (AUROCs), respectively, were 0.87 (0.83-0.89), 0.85 (0.83-0.87), 0.89 (0.86 – 0.92), 0.84 (0.80-0.89), and 0.86 (0.83-0.90). The area under the precision recall curves (AUPRCs), respectively, were 0.29 (0.25-0.37), 0.17 (0.13-0.22), 0.22 (0.14-0.31), 0.13 (0.08-0.21), and 0.14 (0.09-0.21). The results demonstrated accurate prediction of in-hospital mortality for adult patients at the time of admission. The data elements, methods, and patient selection make the model implementable at a system-level." @default.
• W2966790404 created "2019-08-13" @default.
• W2966790404 creator A5007955926 @default.
• W2966790404 creator A5009455981 @default.
• W2966790404 creator A5012849300 @default.
• W2966790404 creator A5025153342 @default.
• W2966790404 creator A5033019632 @default.
• W2966790404 creator A5044677056 @default.
• W2966790404 creator A5051396123 @default.
• W2966790404 creator A5079293522 @default.
• W2966790404 creator A5080784591 @default.
• W2966790404 creator A5089062751 @default.
• W2966790404 creator A5091696223 @default.
• W2966790404 date "2019-06-26" @default.
• W2966790404 modified "2023-10-16" @default.
• W2966790404 title "Prospective and External Evaluation of a Machine Learning Model to Predict In-Hospital Mortality" @default.
• W2966790404 cites W1966716734 @default.
• W2966790404 cites W1976526581 @default.
• W2966790404 cites W1996796871 @default.
• W2966790404 cites W2033609349 @default.
• W2966790404 cites W2098368369 @default.
• W2966790404 cites W2101351409 @default.
• W2966790404 cites W2103742358 @default.
• W2966790404 cites W2115868670 @default.
• W2966790404 cites W2136085913 @default.
• W2966790404 cites W2311794510 @default.
• W2966790404 cites W2324406228 @default.
• W2966790404 cites W2342178784 @default.
• W2966790404 cites W2464247578 @default.
• W2966790404 cites W2766780106 @default.
• W2966790404 cites W2780831753 @default.
• W2966790404 cites W2793079232 @default.
• W2966790404 cites W2884775595 @default.
• W2966790404 cites W2888424632 @default.
• W2966790404 cites W2899682645 @default.
• W2966790404 cites W2901997892 @default.
• W2966790404 cites W2937186836 @default.
• W2966790404 cites W2942586440 @default.
• W2966790404 cites W3098949126 @default.
• W2966790404 cites W3100279624 @default.
• W2966790404 cites W3102476541 @default.
• W2966790404 doi "https://doi.org/10.1101/19000133" @default.
• W2966790404 hasPublicationYear "2019" @default.
• W2966790404 type Work @default.
• W2966790404 sameAs 2966790404 @default.
• W2966790404 citedByCount "0" @default.
• W2966790404 crossrefType "posted-content" @default.
• W2966790404 hasAuthorship W2966790404A5007955926 @default.
• W2966790404 hasAuthorship W2966790404A5009455981 @default.
• W2966790404 hasAuthorship W2966790404A5012849300 @default.
• W2966790404 hasAuthorship W2966790404A5025153342 @default.
• W2966790404 hasAuthorship W2966790404A5033019632 @default.
• W2966790404 hasAuthorship W2966790404A5044677056 @default.
• W2966790404 hasAuthorship W2966790404A5051396123 @default.
• W2966790404 hasAuthorship W2966790404A5079293522 @default.
• W2966790404 hasAuthorship W2966790404A5080784591 @default.
• W2966790404 hasAuthorship W2966790404A5089062751 @default.
• W2966790404 hasAuthorship W2966790404A5091696223 @default.
• W2966790404 hasBestOaLocation W29667904041 @default.
• W2966790404 hasConcept C100660578 @default.
• W2966790404 hasConcept C112705442 @default.
• W2966790404 hasConcept C119857082 @default.
• W2966790404 hasConcept C126322002 @default.
• W2966790404 hasConcept C138885662 @default.
• W2966790404 hasConcept C141071460 @default.
• W2966790404 hasConcept C154945302 @default.
• W2966790404 hasConcept C188816634 @default.
• W2966790404 hasConcept C194828623 @default.
• W2966790404 hasConcept C3020225094 @default.
• W2966790404 hasConcept C41008148 @default.
• W2966790404 hasConcept C41895202 @default.
• W2966790404 hasConcept C58471807 @default.
• W2966790404 hasConcept C71924100 @default.
• W2966790404 hasConcept C76318530 @default.
• W2966790404 hasConceptScore W2966790404C100660578 @default.
• W2966790404 hasConceptScore W2966790404C112705442 @default.
• W2966790404 hasConceptScore W2966790404C119857082 @default.
• W2966790404 hasConceptScore W2966790404C126322002 @default.
• W2966790404 hasConceptScore W2966790404C138885662 @default.
• W2966790404 hasConceptScore W2966790404C141071460 @default.
• W2966790404 hasConceptScore W2966790404C154945302 @default.
• W2966790404 hasConceptScore W2966790404C188816634 @default.
• W2966790404 hasConceptScore W2966790404C194828623 @default.
• W2966790404 hasConceptScore W2966790404C3020225094 @default.
• W2966790404 hasConceptScore W2966790404C41008148 @default.
• W2966790404 hasConceptScore W2966790404C41895202 @default.
• W2966790404 hasConceptScore W2966790404C58471807 @default.
• W2966790404 hasConceptScore W2966790404C71924100 @default.
• W2966790404 hasConceptScore W2966790404C76318530 @default.
• W2966790404 hasLocation W29667904041 @default.
• W2966790404 hasLocation W29667904042 @default.
• W2966790404 hasOpenAccess W2966790404 @default.
• W2966790404 hasPrimaryLocation W29667904041 @default.
• W2966790404 hasRelatedWork W1965797730 @default.
• W2966790404 hasRelatedWork W2200122354 @default.
• W2966790404 hasRelatedWork W2790694493 @default.
• W2966790404 hasRelatedWork W2889592693 @default.
• W2966790404 hasRelatedWork W2903156192 @default.
• W2966790404 hasRelatedWork W2929110666 @default.
• W2966790404 hasRelatedWork W2938555257 @default.

• next