FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W4319067564> ?p ?o ?g. }

• W4319067564 endingPage "21" @default.
• W4319067564 startingPage "13" @default.
• W4319067564 abstract "Abstract Objectives The shortage of grafts for liver transplantation requires risk stratification and adequate allocation rules. This study aims to improve the model of end-stage liver disease (MELD) score for 90-day mortality prediction with the help of different machine-learning algorithms. Methods We retrospectively analyzed the clinical and laboratory data of 654 patients who were recruited during the evaluation process for liver transplantation at University Hospital Leipzig. After comparing 13 different machine-learning algorithms in a nested cross-validation setting and selecting the best performing one, we built a new model to predict 90-day mortality in patients with end-stage liver disease. Results Penalized regression algorithms yielded the highest prediction performance in our machine-learning algorithm benchmark. In favor of a simpler model, we chose the least absolute shrinkage and selection operator (lasso) regression. Beside the classical MELD international normalized ratio (INR) and bilirubin, the lasso regression selected cystatin C over creatinine, as well as IL-6, total protein, and cholinesterase. The new model offers improved discrimination and calibration over MELD and MELD with sodium (MELD-Na), MELD 3.0, or the MELD-Plus7 risk score. Conclusions We provide a new machine-learning-based model of end-stage liver disease that incorporates synthesis and inflammatory markers and may improve the classical MELD score for 90-day survival prediction." @default.
• W4319067564 created "2023-02-04" @default.
• W4319067564 creator A5038100282 @default.
• W4319067564 creator A5060564118 @default.
• W4319067564 creator A5079955260 @default.
• W4319067564 creator A5082309779 @default.
• W4319067564 creator A5082969689 @default.
• W4319067564 date "2023-02-01" @default.
• W4319067564 modified "2023-09-26" @default.
• W4319067564 title "A new machine-learning-based prediction of survival in patients with end-stage liver disease" @default.
• W4319067564 cites W1570622790 @default.
• W4319067564 cites W1602160603 @default.
• W4319067564 cites W1965801346 @default.
• W4319067564 cites W2021733365 @default.
• W4319067564 cites W2063575396 @default.
• W4319067564 cites W2067431366 @default.
• W4319067564 cites W2084139018 @default.
• W4319067564 cites W2114586150 @default.
• W4319067564 cites W2125103962 @default.
• W4319067564 cites W2129925362 @default.
• W4319067564 cites W2140396673 @default.
• W4319067564 cites W2149199519 @default.
• W4319067564 cites W2157076315 @default.
• W4319067564 cites W2158121233 @default.
• W4319067564 cites W2162322495 @default.
• W4319067564 cites W2314611774 @default.
• W4319067564 cites W2412506465 @default.
• W4319067564 cites W2753919178 @default.
• W4319067564 cites W2753962694 @default.
• W4319067564 cites W2767127749 @default.
• W4319067564 cites W2996717911 @default.
• W4319067564 cites W3012979212 @default.
• W4319067564 cites W3034804273 @default.
• W4319067564 cites W3099478002 @default.
• W4319067564 cites W3102027041 @default.
• W4319067564 cites W3102476541 @default.
• W4319067564 cites W3111736660 @default.
• W4319067564 cites W3134934150 @default.
• W4319067564 cites W3137775641 @default.
• W4319067564 cites W3147894994 @default.
• W4319067564 cites W3168924500 @default.
• W4319067564 cites W3197129141 @default.
• W4319067564 cites W4280541509 @default.
• W4319067564 cites W2587085619 @default.
• W4319067564 doi "https://doi.org/10.1515/labmed-2022-0162" @default.
• W4319067564 hasPublicationYear "2023" @default.
• W4319067564 type Work @default.
• W4319067564 citedByCount "0" @default.
• W4319067564 crossrefType "journal-article" @default.
• W4319067564 hasAuthorship W4319067564A5038100282 @default.
• W4319067564 hasAuthorship W4319067564A5060564118 @default.
• W4319067564 hasAuthorship W4319067564A5079955260 @default.
• W4319067564 hasAuthorship W4319067564A5082309779 @default.
• W4319067564 hasAuthorship W4319067564A5082969689 @default.
• W4319067564 hasBestOaLocation W43190675641 @default.
• W4319067564 hasConcept C105795698 @default.
• W4319067564 hasConcept C11413529 @default.
• W4319067564 hasConcept C119857082 @default.
• W4319067564 hasConcept C126322002 @default.
• W4319067564 hasConcept C13280743 @default.
• W4319067564 hasConcept C136764020 @default.
• W4319067564 hasConcept C154945302 @default.
• W4319067564 hasConcept C185798385 @default.
• W4319067564 hasConcept C205649164 @default.
• W4319067564 hasConcept C2777075537 @default.
• W4319067564 hasConcept C2779250428 @default.
• W4319067564 hasConcept C2779609443 @default.
• W4319067564 hasConcept C2780306776 @default.
• W4319067564 hasConcept C2911091166 @default.
• W4319067564 hasConcept C33923547 @default.
• W4319067564 hasConcept C37616216 @default.
• W4319067564 hasConcept C41008148 @default.
• W4319067564 hasConcept C71924100 @default.
• W4319067564 hasConcept C83546350 @default.
• W4319067564 hasConceptScore W4319067564C105795698 @default.
• W4319067564 hasConceptScore W4319067564C11413529 @default.
• W4319067564 hasConceptScore W4319067564C119857082 @default.
• W4319067564 hasConceptScore W4319067564C126322002 @default.
• W4319067564 hasConceptScore W4319067564C13280743 @default.
• W4319067564 hasConceptScore W4319067564C136764020 @default.
• W4319067564 hasConceptScore W4319067564C154945302 @default.
• W4319067564 hasConceptScore W4319067564C185798385 @default.
• W4319067564 hasConceptScore W4319067564C205649164 @default.
• W4319067564 hasConceptScore W4319067564C2777075537 @default.
• W4319067564 hasConceptScore W4319067564C2779250428 @default.
• W4319067564 hasConceptScore W4319067564C2779609443 @default.
• W4319067564 hasConceptScore W4319067564C2780306776 @default.
• W4319067564 hasConceptScore W4319067564C2911091166 @default.
• W4319067564 hasConceptScore W4319067564C33923547 @default.
• W4319067564 hasConceptScore W4319067564C37616216 @default.
• W4319067564 hasConceptScore W4319067564C41008148 @default.
• W4319067564 hasConceptScore W4319067564C71924100 @default.
• W4319067564 hasConceptScore W4319067564C83546350 @default.
• W4319067564 hasFunder F4320323752 @default.
• W4319067564 hasIssue "1" @default.
• W4319067564 hasLocation W43190675641 @default.
• W4319067564 hasOpenAccess W4319067564 @default.
• W4319067564 hasPrimaryLocation W43190675641 @default.

• next